System for cell-based screening

ABSTRACT

The present invention provides systems, methods, screens, reagents and kits for optical system analysis of cells to rapidly determine the distribution, environment, or activity of fluorescently labeled reporter molecules in cells for the purpose of screening large numbers of compounds for those that specifically affect neurite outgrowth.

CROSS REFERENCE

This application claims priority from U.S. Provisional PatentApplication Ser. Nos. 60/147,443 filed Aug. 5, 1999; 60/176,589 filedJan. 18, 2000; and 60/205,696 filed May 19, 2000; and is acontinuation-in-part of U.S. applications for patent Ser. No. 09/398,965filed Sep. 17, 1999; which is a continuation in part of Ser. No.09/031,271 filed Feb. 27, 1998 which is a continuation in part of U.S.application Ser. No. 08/810,983, filed on Feb. 27, 1997, now U.S. Pat.No. 5,989,835; and is related to commonly owned and co-pending U.S.patent application Ser. No. 09/380,259 filed Feb. 27, 1998; Ser. No.09/352,171 filed Jul. 12, 1999; Ser. No. 09/598,347 filed Jun. 21, 2000;Ser. No. 09/293,209 filed Apr. 16, 1999; Ser. No. 09/293,210 filed Apr.16, 1999; Ser. No. 09/398,965 filed Sep. 17, 1999; Ser. No. 09/430,656filed Oct. 29, 1999; Ser. No. 09/513,783 filed Feb. 25, 2000; and Ser.No. 09/569,508 filed May 12, 2000; all references incorporated byreference herein in their entirety.

FIELD OF THE INVENTION

This invention is in the field of fluorescence-based cell and molecularbiochemical assays for drug discovery.

BACKGROUND OF THE INVENTION

Drug discovery, as currently practiced in the art, is a long, multiplestep process involving identification of specific disease targets,development of an assay based on a specific target, validation of theassay, optimization and automation of the assay to produce a screen,high throughput screening of compound libraries using the assay toidentify “hits”, hit validation and hit compound optimization. Theoutput of this process is a lead compound that goes into pre-clinicaland, if validated, eventually into clinical trials. In this process, thescreening phase is distinct from the assay development phases, andinvolves testing compound efficacy in living biological systems.

Historically, drug discovery is a slow and costly process, spanningnumerous years and consuming hundreds of millions of dollars per drugcreated. Developments in the areas of genomics and high throughputscreening have resulted in increased capacity and efficiency in theareas of target identification and volume of compounds screened.Significant advances in automated DNA sequencing, PCR application,positional cloning, hybridization arrays, and bioinformatics havegreatly increased the number of genes (and gene fragments) encodingpotential drug screening targets. However, the basic scheme for drugscreening remains the same.

Validation of genomic targets as points for therapeutic interventionusing the existing methods and protocols has become a bottleneck in thedrug discovery process due to the slow, manual methods employed, such asin vivo functional models, functional analysis of recombinant proteins,and stable cell line expression of candidate genes. Primary DNA sequencedata acquired through automated sequencing does not permitidentification of gene function, but can provide information aboutcommon “motifs” and specific gene homology when compared to knownsequence databases. Genomic methods such as subtraction hybridizationand RADE (rapid amplification of differential expression) can be used toidentify genes that are up or down regulated in a disease state model.However, identification and validation still proceed down the samepathway. Some proteomic methods use protein identification (globalexpression arrays, 2D electrophoresis, combinatorial libraries) incombination with reverse genetics to identify candidate genes ofinterest. Such putative “disease associated sequences” or DAS isolatedas intact cDNA are a great advantage to these methods, but they areidentified by the hundreds without providing any information regardingtype, activity, and distribution of the encoded protein. Choosing asubset of DAS as drug screening targets is “random”, and thus extremelyinefficient, without functional data to provide a mechanistic link withdisease. It is necessary, therefore, to provide new technologies torapidly screen DAS to establish biological function, thereby improvingtarget validation and candidate optimization in drug discovery.

There are three major avenues for improving early drug discoveryproductivity. First, there is a need for tools that provide increasedinformation handling capability. Bioinformatics has blossomed with therapid development of DNA sequencing systems and the evolution of thegenomics database. Genomics is beginning to play a critical role in theidentification of potential new targets. Proteomics has becomeindispensable in relating structure and function of protein targets inorder to predict drug interactions. However, the next level ofbiological complexity is the cell. Therefore, there is a need toacquire, manage and search multidimensional information from cells.Secondly, there is a need for higher throughput tools. Automation is akey to improving productivity as has already been demonstrated in DNAsequencing and high throughput primary screening. The instant inventionprovides for automated systems that extract multiple parameterinformation from cells that meet the need for higher throughput tools.The instant invention also provides for miniaturizing the methods,thereby allowing increased throughput, while decreasing the volumes ofreagents and test compounds required in each assay.

Radioactivity has been the dominant read-out in early drug discoveryassays. However, the need for more information, higher throughput andminiaturization has caused a shift towards using fluorescence detection.Fluorescence-based reagents can yield more powerful, multiple parameterassays that are higher in throughput and information content and requirelower volumes of reagents and test compounds. Fluorescence is also saferand less expensive than radioactivity-based methods.

Screening of cells treated with dyes and fluorescent reagents is wellknown in the art. There is a considerable body of literature related togenetic engineering of cells to produce fluorescent proteins, such asmodified green fluorescent protein (GFP), as a reporter molecule. Someproperties of wild-type GFP are disclosed by Morise et al. (Biochemistry13 (1974), p. 2656-2662), and Ward et al. (Photochem. Photobiol. 31(1980), p. 611-615). The GFP of the jellyfish Aequorea Victoria has anexcitation maximum at 395 nm and an emission maximum at 510 nm, and doesnot require an exogenous factor for fluorescence activity. Uses for GFPdisclosed in the literature are widespread and include the study of geneexpression and protein localization (Chalfie et al., Science 263 (1994),p. 12501-12504)), as a tool for visualizing subcellular organelles(Rizzuto et al., Curr. Biology 5 (1995), p. 635-642)), visualization ofprotein transport along the secretory pathway (Kaether and Gerdes, FEBSLetters 369 (1995), p. 267-271)), expression in plant cells (Hu andCheng, FEBS Letters 369 (1995), p. 331-334)) and Drosophila embryos(Davis et al., Dev. Biology 170 (1995), p. 726-729)), and as a reportermolecule fused to another protein of interest (U.S. Pat. No. 5,491,084).Similarly, WO96/23898 relates to methods of detecting biologicallyactive substances affecting intracellular processes by utilizing a GFPconstruct having a protein kinase activation site. This patent, and allother patents referenced in this application are incorporated byreference in their entirety

Numerous references are related to GFP proteins in biological systems.For example, WO 96/09598 describes a system for isolating cells ofinterest utilizing the expression of a GFP like protein. WO 96/27675describes the expression of GFP in plants. WO 95/21191 describesmodified GFP protein expressed in transformed organisms to detectmutagenesis. U.S. Pat. Nos. 5,401,629 and 5,436,128 describe assays andcompositions for detecting and evaluating the intracellular transductionof an extracellular signal using recombinant cells that express cellsurface receptors and contain reporter gene constructs that includetranscriptional regulatory elements that are responsive to the activityof cell surface receptors.

Performing a screen on many thousands of compounds requires parallelhandling and processing of many compounds and assay component reagents.Standard high throughput screens (“HTS”) use mixtures of compounds andbiological reagents along with some indicator compound loaded intoarrays of wells in standard microtiter plates with 96 or 384 wells. Thesignal measured from each well, either fluorescence emission, opticaldensity, or radioactivity, integrates the signal from all the materialin the well giving an overall population average of all the molecules inthe well.

Science Applications International Corporation (SAIC) 130 Fifth Avenue,Seattle, Wash. 98109) describes an imaging plate reader. This systemuses a CCD camera to image the whole area of a 96 well plate. The imageis analyzed to calculate the total fluorescence per well for all thematerial in the well.

Molecular Devices, Inc. (Sunnyvale, Calif.) describes a system (FLIPR)which uses low angle laser scanning illumination and a mask toselectively excite fluorescence within approximately 200 microns of thebottoms of the wells in standard 96 well plates in order to reducebackground when imaging cell monolayers. This system uses a CCD camerato image the whole area of the plate bottom. Although this systemmeasures signals originating from a cell monolayer at the bottom of thewell, the signal measured is averaged over the area of the well and istherefore still considered a measurement of the average response of apopulation of cells. The image is analyzed to calculate the totalfluorescence per well for cell-based assays. Fluid delivery devices havealso been incorporated into cell based screening systems, such as theFLIPR system, in order to initiate a response, which is then observed asa whole well population average response using a macro-imaging system.

In contrast to high throughput screens, various high-content screens(“HCS”) have been developed to address the need for more detailedinformation about the temporal-spatial dynamics of cell constituents andprocesses. High-content screens automate the extraction of multicolorfluorescence information derived from specific fluorescence-basedreagents incorporated into cells (Giuliano and Taylor (1995), Curr. Op.Cell Biol. 7:4; Giuliano et al. (1995) Ann. Rev. Biophys. Biomol.Struct. 24:405). Cells are analyzed using an optical system that canmeasure spatial, as well as temporal dynamics. (Farkas et al. (1993)Ann. Rev. Physiol. 55:785; Giuliano et al. (1990) In Optical Microscopyfor Biology. B. Herman and K. Jacobson (eds.), pp. 543-557. Wiley-Liss,New York; Hahn et al (1992) Nature 359:736; Waggoner et al. (1996) Hum.Pathol. 27:494). The concept is to treat each cell as a “well” that hasspatial and temporal information on the activities of the labeledconstituents.

The types of biochemical and molecular information now accessiblethrough fluorescence-based reagents applied to cells include ionconcentrations, membrane potential, specific translocations, enzymeactivities, gene expression, as well as the presence, amounts andpatterns of metabolites, proteins, lipids, carbohydrates, and nucleicacid sequences (DeBiasio et al., (1996) Mol. Biol. Cell. 7:1259;Giuliano et al., (1995) Ann. Rev. Biophys. Biomol. Struct. 24:405; Heimand Tsien, (1996) Curr. Biol. 6:178).

High-content screens can be performed on either fixed cells, usingfluorescently labeled antibodies, biological ligands, and/or nucleicacid hybridization probes, or live cells using multicolor fluorescentindicators and “biosensors.” The choice of fixed or live cell screensdepends on the specific cell-based assay required.

Fixed cell assays are the simplest, since an array of initially livingcells in a microtiter plate format can be treated with various compoundsand doses being tested, then the cells can be fixed, labeled withspecific reagents, and measured. No environmental control of the cellsis required after fixation. Spatial information is acquired, but only atone time point. The availability of thousands of antibodies, ligands andnucleic acid hybridization probes that can be applied to cells makesthis an attractive approach for many types of cell-based screens. Thefixation and labeling steps can be automated, allowing efficientprocessing of assays.

Live cell assays are more sophisticated and powerful, since an array ofliving cells containing the desired reagents can be screened over time,as well as space. Environmental control of the cells (temperature,humidity, and carbon dioxide) is required during measurement, since thephysiological health of the cells must be maintained for multiplefluorescence measurements over time. There is a growing list offluorescent physiological indicators and “biosensors” that can reportchanges in biochemical and molecular activities within cells (Giulianoet al., (1995) Ann. Rev. Biophys. Biomol. Struct. 24:405; Hahn et al.,(1993) In Fluorescent and Luminescent Probes for Biological Activity. W.T. Mason, (ed.), pp. 349-359, Academic Press, San Diego).

The availability and use of fluorescence-based reagents has helped toadvance the development of both fixed and live cell high-contentscreens. Advances in instrumentation to automatically extractmulticolor, high-content information has recently made it possible todevelop HCS into an automated tool. An article by Taylor, et al.(American Scientist 80 (1992), p. 322-335) describes many of thesemethods and their applications. For example, Proffitt et. al. (Cytometry24: 204-213 (1996)) describe a semi-automated fluorescence digitalimaging system for quantifying relative cell numbers in situ in avariety of tissue culture plate formats, especially 96-well microtiterplates. The system consists of an epifluorescence inverted microscopewith a motorized stage, video camera, image intensifier, and amicrocomputer with a PC-Vision digitizer. Turbo Pascal software controlsthe stage and scans the plate taking multiple images per well. Thesoftware calculates total fluorescence per well, provides for dailycalibration, and configures easily for a variety of tissue culture plateformats. Thresholding of digital images and reagents which fluoresceonly when taken up by living cells are used to reduce backgroundfluorescence without removing excess fluorescent reagent.

Scanning confocal microscope imaging (Go et al., (1997) AnalyticalBiochemistry 247:210-215; Goldman et al., (1995) Experimental CellResearch 221:311-319) and multiphoton microscope imaging (Denk et al.,(1990) Science 248:73; Gratton et al., (1994) Proc. of the MicroscopicalSociety of America, pp. 154-155) are also well established methods foracquiring high resolution images of microscopic samples. The principleadvantage of these optical systems is the very shallow depth of focus,which allows features of limited axial extent to be resolved against thebackground. For example, it is possible to resolve internal cytoplasmicfeatures of adherent cells from the features on the cell surface.Because scanning multiphoton imaging requires very short duration pulsedlaser systems to achieve the high photon flux required, fluorescencelifetimes can also be measured in these systems (Lakowicz et al., (1992)Anal. Biochem. 202:316-330; Gerrittsen et al. (1997), J. of Fluorescence7:11-15)), providing additional capability for different detectionmodes. Small, reliable and relatively inexpensive laser systems, such aslaser diode pumped lasers, are now available to allow multiphotonconfocal microscopy to be applied in a fairly routine fashion.

A combination of the biological heterogeneity of cells in populations(Bright, et al., (1989). J. Cell. Physiol. 141:410; Giuliano, (1996)Cell Motil. Cytoskel. 35:237)) as well as the high spatial and temporalfrequency of chemical and molecular information present within cells,makes it impossible to extract high-content information from populationsof cells using existing whole microtiter plate readers. No existinghigh-content screening platform has been designed for multicolor,fluorescence-based screens using cells that are analyzed individually.Similarly, no method is currently available that combines automatedfluid delivery to arrays of cells for the purpose of systematicallyscreening compounds for the ability to induce a cellular response thatis identified by HCS analysis, especially from cells grown in microtiterplates. Furthermore, no method exists in the art combining highthroughput well-by-well measurements to identify “hits” in one assayfollowed by a second high content cell-by-cell measurement on the sameplate of only those wells identified as hits.

The instant invention provides systems, methods, and screens thatcombine high throughput screening (HTS) and high content screening (HCS)that significantly improve target validation and candidate optimizationby combining many cell screening formats with fluorescence-basedmolecular reagents and computer-based feature extraction, data analysis,and automation, resulting in increased quantity and speed of datacollection, shortened cycle times, and, ultimately, faster evaluation ofpromising drug candidates. The instant invention also provides forminiaturizing the methods, thereby allowing increased throughput, whiledecreasing the volumes of reagents and test compounds required in eachassay.

SUMMARY OF THE INVENTION

In one aspect, the present invention relates to a method for analyzingcells comprising

-   -   providing cells containing fluorescent reporter molecules in an        array of locations,    -   treating the cells in the array of locations with one or more        reagents,    -   imaging numerous cells in each location with fluorescence        optics,    -   converting the optical information into digital data,    -   utilizing the digital data to determine the distribution,        environment or activity of the fluorescently labeled reporter        molecules in the cells and the distribution of the cells, and    -   interpreting that information in terms of a positive, negative        or null effect of the compound being tested on the biological        function

In this embodiment, the method rapidly determines the distribution,environment, or activity of fluorescently labeled reporter molecules incells for the purpose of screening large numbers of compounds for thosethat specifically affect particular biological functions. The array oflocations may be a microtiter plate or a microchip which is a microplatehaving cells in an array of locations. In a preferred embodiment, themethod includes computerized means for acquiring, processing, displayingand storing the data received. In a preferred embodiment, the methodfurther comprises automated fluid delivery to the arrays of cells. Inanother preferred embodiment, the information obtained from highthroughput measurements on the same plate are used to selectivelyperform high content screening on only a subset of the cell locations onthe plate.

In another aspect of the present invention, a cell screening system isprovided that comprises:

-   -   a high magnification fluorescence optical system having a        microscope objective,    -   an XY stage adapted for holding a plate containing an array of        cells and having a means for moving the plate for proper        alignment and focusing on the cell arrays;    -   a digital camera;    -   a light source having optical means for directing excitation        light to cell arrays and a means for directing fluorescent light        emitted from the cells to the digital camera; and    -   a computer means for receiving and processing digital data from        the digital camera wherein the computer means includes a digital        frame grabber for receiving the images from the camera, a        display for user interaction and display of assay results,        digital storage media for data storage and archiving, and a        means for control, acquisition, processing and display of        results.

In a preferred embodiment, the cell screening system further comprises acomputer screen operatively associated with the computer for displayingdata. In another preferred embodiment, the computer means for receivingand processing digital data from the digital camera stores the data in abioinformatics data base. In a further preferred embodiment, the cellscreening system further comprises a reader that measures a signal frommany or all the wells in parallel. In another preferred embodiment, thecell screening system further comprises a mechanical-optical means forchanging the magnification of the system, to allow changing modesbetween high throughput and high content screening. In another preferredembodiment, the cell screening system further comprises a chamber andcontrol system to maintain the temperature, CO₂ concentration andhumidity surrounding the plate at levels required to keep cells alive.In a further preferred embodiment, the cell screening system utilizes aconfocal scanning illumination and detection system.

In another aspect of the present invention, a machine readable storagemedium comprising a program containing a set of instructions for causinga cell screening system to execute procedures for defining thedistribution and activity of specific cellular constituents andprocesses is provided. In a preferred embodiment, the cell screeningsystem comprises a high magnification fluorescence optical system with astage adapted for holding cells and a means for moving the stage, adigital camera, a light source for receiving and processing the digitaldata from the digital camera, and a computer means for receiving andprocessing the digital data from the digital camera. Preferredembodiments of the machine readable storage medium comprise programsconsisting of a set of instructions for causing a cell screening systemto execute the procedures set forth in FIGS. 9, 11, 12, 13, 14 or 15.Another preferred embodiment comprises a program consisting of a set ofinstructions for causing a cell screening system to execute proceduresfor detecting the distribution and activity of specific cellularconstituents and processes. In most preferred embodiments, the cellularprocesses include, but are not limited to, nuclear translocation of aprotein, cellular hypertrophy, apoptosis, and protease-inducedtranslocation of a protein.

In another preferred embodiment, a variety of automated cell screeningmethods are provided, including screens to analyze and to identifycompounds that affect transcription factor activity, protein kinaseactivity, cell morphology, microtubule structure, apoptosis, receptorinternalization, protease-induced translocation of a protein, andneurite outgrowth.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a diagram of the components of the cell-based scanningsystem.

FIG. 2 shows a schematic of the microscope subassembly.

FIG. 3 shows the camera subassembly.

FIG. 4 illustrates cell scanning system process.

FIG. 5 illustrates a user interface showing major functions to guide theuser.

FIG. 6 is a block diagram of the two platform architecture of the DualMode System for Cell Based Screening in which one platform uses atelescope lens to read all wells of a microtiter plate and a secondplatform that uses a higher magnification lens to read individual cellsin a well.

FIG. 7 is a detail of an optical system for a single platformarchitecture of the Dual Mode System for Cell Based Screening that usesa moveable ‘telescope’ lens to read all wells of a microtiter plate anda moveable higher magnification lens to read individual cells in a well.

FIG. 8 is an illustration of the fluid delivery system for acquiringkinetic data on the Cell Based Screening System.

FIG. 9 is a flow chart of processing step for the cell-based scanningsystem.

FIG. 10 A-J illustrates the strategy of the Nuclear Translocation Assay.

FIG. 11 is a flow chart defining the processing steps in the Dual ModeSystem for Cell Based Screening combining high throughput and highcontent screening of microtiter plates.

FIG. 12 is a flow chart defining the processing steps in the HighThroughput mode of the System for Cell Based Screening.

FIG. 13 is a flow chart defining the processing steps in the HighContent mode of the System for Cell Based Screening.

FIG. 14 is a flow chart defining the processing steps required foracquiring kinetic data in the High Content mode of the System for CellBased Screening.

FIG. 15 is a flow chart defining the processing steps performed within awell during the acquisition of kinetic data

FIG. 16 is an example of data from a known inhibitor of translocation.

FIG. 17 is an example of data from a known stimulator of translocation.

FIG. 18 illustrates data presentation on a graphical display.

FIG. 19 is an illustration of the data from the High Throughput mode ofthe System for Cell Based Screening, an example of the data passed tothe High Content mode, the data acquired in the high content mode, andthe results of the analysis of that data.

FIG. 20 shows the measurement of a drug-induced cytoplasm to nucleartranslocation.

FIG. 21 illustrates a graphical user interface of the measurement shownin FIG. 20.

FIG. 22 illustrates a graphical user interface, with data presentation,of the measurement shown in FIG. 20.

FIG. 23 is a graph representing the kinetic data obtained from themeasurements depicted in FIG. 20.

FIG. 24 details a high-content screen of drug-induced apoptosis.

FIG. 25 (A) Flowchart of image acquisition initialization phase; (B)Flowchart of image acquisition iteration phase.

FIG. 26 is a flowchart of the Positive State Detection ThresholdComputation.

FIG. 27 is a flowchart of Neurite Outgrowth Alternative QuantificationMethod. (A) Neuronal Nuclei Identification; (B) Neurite OutgrowthQuantification.

FIG. 28 is a flowchart of the Cell State Detection Method (MorphologicalMethod).

FIG. 29 is a flowchart of the Cell State Detection Method (Blob AnalysisMethod).

DETAILED DESCRIPTION OF THE INVENTION

All cited patents, patent applications and other references are herebyincorporated by reference in their entirety.

As used herein, the following terms have the specified meaning:

Markers of cellular domains. Luminescent probes that have high affinityfor specific cellular constituents including specific organelles ormolecules. These probes can either be small luminescent molecules orfluorescently tagged macromolecules used as “labeling reagents”,“environmental indicators”, or “biosensors.”

Labeling reagents. Labeling reagents include, but are not limited to,luminescently labeled macromolecules including fluorescent proteinanalogs and biosensors, luminescent macromolecular chimeras includingthose formed with the green fluorescent protein and mutants thereof,luminescently labeled primary or secondary antibodies that react withcellular antigens involved in a physiological response, luminescentstains, dyes, and other small molecules.

Markers of cellular translocations. Luminescently tagged macromoleculesor organelles that move from one cell domain to another during somecellular process or physiological response. Translocation markers caneither simply report location relative to the markers of cellulardomains or they can also be “biosensors” that report some biochemical ormolecular activity as well.

Biosensors. Macromolecules consisting of a biological functional domainand a luminescent probe or probes that report the environmental changesthat occur either internally or on their surface. A class ofluminescently labeled macromolecules designed to sense and report thesechanges have been termed “fluorescent-protein biosensors”. The proteincomponent of the biosensor provides a highly evolved molecularrecognition moiety. A fluorescent molecule attached to the proteincomponent in the proximity of an active site transduces environmentalchanges into fluorescence signals that are detected using a system withan appropriate temporal and spatial resolution such as the cell scanningsystem of the present invention. Because the modulation of nativeprotein activity within the living cell is reversible, and becausefluorescent-protein biosensors can be designed to sense reversiblechanges in protein activity, these biosensors are essentially reusable.

Disease associated sequences (“DAS”). This term refers to nucleic acidsequences identified by standard techniques, such as primary DNAsequence data, genomic methods such as subtraction hybridization andRADE, and proteomic methods in combination with reverse genetics, asbeing of drug candidate compounds. The term does not mean that thesequence is only associated with a disease state.

High content screening (HCS) can be used to measure the effects of drugson complex molecular events such as signal transduction pathways, aswell as cell functions including, but not limited to, apoptosis, celldivision, cell adhesion, locomotion, exocytosis, and cell-cellcommunication. Multicolor fluorescence permits multiple targets and cellprocesses to be assayed in a single screen. Cross-correlation ofcellular responses will yield a wealth of information required fortarget validation and lead optimization.

In one aspect of the present invention, a cell screening system isprovided comprising a high magnification fluorescence optical systemhaving a microscope objective, an XY stage adapted for holding a platewith an array of locations for holding cells and having a means formoving the plate to align the locations with the microscope objectiveand a means for moving the plate in the direction to effect focusing; adigital camera; a light source having optical means for directingexcitation light to cells in the array of locations and a means fordirecting fluorescent light emitted from the cells to the digitalcamera; and a computer means for receiving and processing digital datafrom the digital camera wherein the computer means includes: a digitalframe grabber for receiving the images from the camera, a display foruser interaction and display of assay results, digital storage media fordata storage and archiving, and means for control, acquisition,processing and display of results.

FIG. 1 is a schematic diagram of a preferred embodiment of the cellscanning system. An inverted fluorescence microscope is used 1, such asa Zeiss Axiovert inverted fluorescence microscope which uses standardobjectives with magnification of 1-100× to the camera, and a white lightsource (e.g. 100 W mercury-arc lamp or 75 W xenon lamp) with powersupply 2. There is an XY stage 3 to move the plate 4 in the XY directionover the microscope objective. A Z-axis focus drive 5 moves theobjective in the Z direction for focusing. A joystick 6 provides formanual movement of the stage in the XYZ direction. A high resolutiondigital camera 7 acquires images from each well or location on theplate. There is a camera power supply 8, an automation controller 9 anda central processing unit 10. The PC 11 provides a display 12 and hasassociated software. The printer 13 provides for printing of a hard copyrecord.

FIG. 2 is a schematic of one embodiment of the microscope assembly 1 ofthe invention, showing in more detail the XY stage 3, Z-axis focus drive5, joystick 6, light source 2, and automation controller 9. Cables tothe computer 15 and microscope 16, respectively, are provided. Inaddition, FIG. 2 shows a 96 well microtiter plate 17 which is moved onthe XY stage 3 in the XY direction. Light from the light source 2 passesthrough the PC controlled shutter 18 to a motorized filter wheel 19 withexcitation filters 20. The light passes into filter cube 25 which has adichroic mirror 26 and an emission filter 27. Excitation light reflectsoff the dichroic mirror to the wells in the microtiter plate 17 andfluorescent light 28 passes through the dichroic mirror 26 and theemission filter 27 and to the digital camera 7.

FIG. 3 shows a schematic drawing of a preferred camera assembly. Thedigital camera 7, which contains an automatic shutter for exposurecontrol and a power supply 31, receives fluorescent light 28 from themicroscope assembly. A digital cable 30 transports digital signals tothe computer.

The standard optical configurations described above use microscopeoptics to directly produce an enlarged image of the specimen on thecamera sensor in order to capture a high resolution image of thespecimen. This optical system is commonly referred to as ‘wide field’microscopy. Those skilled in the art of microscopy will recognize that ahigh resolution image of the specimen can be created by a variety ofother optical systems, including, but not limited to, standard scanningconfocal detection of a focused point or line of illumination scannedover the specimen (Go et al. 1997, supra), and multi-photon scanningconfocal microscopy (Denk et al., 1990, supra), both of which can formimages on a CCD detector or by synchronous digitization of the analogoutput of a photomultiplier tube.

In screening applications, it is often necessary to use a particularcell line, or primary cell culture, to take advantage of particularfeatures of those cells. Those skilled in the art of cell culture willrecognize that some cell lines are contact inhibited, meaning that theywill stop growing when they become surrounded by other cells, whileother cell lines will continue to grow under those conditions and thecells will literally pile up, forming many layers. An example of such acell line is the HEK 293 (ATCC CRL-1573) line. An optical system thatcan acquire images of single cell layers in multilayer preparations isrequired for use with cell lines that tend to form layers. The largedepth of field of wide field microscopes produces an image that is aprojection through the many layers of cells, making analysis ofsubcellular spatial distributions extremely difficult in layer-formingcells. Alternatively, the very shallow depth of field that can beachieved on a confocal microscope, (about one micron), allowsdiscrimination of a single cell layer at high resolution, simplifyingthe determination of the subcellular spatial distribution. Similarly,confocal imaging is preferable when detection modes such as fluorescencelifetime imaging are required.

The output of a standard confocal imaging attachment for a microscope isa digital image that can be converted to the same format as the imagesproduced by the other cell screening system embodiments described above,and can therefore be processed in exactly the same way as those images.The overall control, acquisition and analysis in this embodiment isessentially the same. The optical configuration of the confocalmicroscope system, is essentially the same as that described above,except for the illuminator and detectors. Illumination and detectionsystems required for confocal microscopy have been designed asaccessories to be attached to standard microscope optical systems suchas that of the present invention (Zeiss, Germany). These alternativeoptical systems therefore can be easily integrated into the system asdescribed above.

FIG. 4 illustrates an alternative embodiment of the invention in whichcell arrays are in microwells 40 on a microplate 41, described ionco-pending U.S. application Ser. No. 08/865,341, incorporated byreference herein in its entirety. Typically the microplate is 20 mm by30 mm as compared to a standard 96 well microtiter plate which is 86 mmby 129 mm. The higher density array of cells on a microplate allows themicroplate to be imaged at a low resolution of a few microns per pixelfor high throughput and particular locations on the microplate to beimaged at a higher resolution of less than 0.5 microns per pixel. Thesetwo resolution modes help to improve the overall throughput of thesystem.

The microplate chamber 42 serves as a microfluidic delivery system forthe addition of compounds to cells. The microplate 41 in the microplatechamber 42 is placed in an XY microplate reader 43. Digital data isprocessed as described above. The small size of this microplate systemincreases throughput, minimizes reagent volume and allows control of thedistribution and placement of cells for fast and precise cell-basedanalysis. Processed data can be displayed on a PC screen 11 and madepart of a bioinformatics data base 44. This data base not only permitsstorage and retrieval of data obtained through the methods of thisinvention, but also permits acquisition and storage of external datarelating to cells. FIG. 5 is a PC display which illustrates theoperation of the software.

In an alternative embodiment, a high throughput system (HTS) is directlycoupled with the HCS either on the same platform or on two separateplatforms connected electronically (e.g. via a local area network). Thisembodiment of the invention, referred to as a dual mode optical system,has the advantage of increasing the throughput of a HCS by coupling itwith a HTS and thereby requiring slower high resolution data acquisitionand analysis only on the small subset of wells that show a response inthe coupled HTS.

High throughput ‘whole plate’ reader systems are well known in the artand are commonly used as a component of an HTS system used to screenlarge numbers of compounds (Beggs (1997), J. of Biomolec. Screening2:71-78; Macaffrey et al., (1996) J. Biomolec. Screening 1:187-190).

In one embodiment of dual mode cell based screening, a two platformarchitecture in which high throughput acquisition occurs on one platformand high content acquisition occurs on a second platform is provided(FIG. 6). Processing occurs on each platform independently, with resultspassed over a network interface, or a single controller is used toprocess the data from both platforms.

As illustrated in FIG. 6, an exemplified two platform dual mode opticalsystem consists of two light optical instruments, a high throughputplatform 60 and a high content platform 65 which read fluorescentsignals emitted from cells cultured in microtiter plates or microwellarrays on a microplate, and communicate with each other via anelectronic connection 64. The high throughput platform 60 analyzes allthe wells in the whole plate either in parallel or rapid serial fashion.Those skilled in the art of screening will recognize that there are amany such commercially available high throughput reader systems thatcould be integrated into a dual mode cell based screening system(Topcount (Packard Instruments, Meriden, Conn.); Spectramax, Lumiskan(Molecular Devices, Sunnyvale, Calif.); Fluoroscan (Labsystems, Beverly,Mass.)). The high content platform 65, as described above, scans fromwell to well and acquires and analyzes high resolution image datacollected from individual cells within a well.

The HTS software, residing on the system's computer 62, controls thehigh throughput instrument, and results are displayed on the monitor 61.The HCS software, residing on it's computer system 67, controls the highcontent instrument hardware 65, optional devices (e.g. plate loader,environmental chamber, fluid dispenser), analyzes digital image datafrom the plate, displays results on the monitor 66 and manages datameasured in an integrated database. The two systems can also share asingle computer, in which case all data would be collected, processedand displayed on that computer, without the need for a local areanetwork to transfer the data. Microtiter plates are transferred from thehigh throughput system to the high content system 63 either manually orby a robotic plate transfer device, as is well known in the art (Beggs(1997), supra; Mcaffrey (1996), supra).

In a preferred embodiment, the dual mode optical system utilizes asingle platform system (FIG. 7). It consists of two separate opticalmodules, an HCS module 203 and an HTS module 209 that can beindependently or collectively moved so that only one at a time is usedto collect data from the microtiter plate 201. The microtiter plate 201is mounted in a motorized X,Y stage so it can be positioned for imagingin either HTS or HCS mode. After collecting and analyzing the HTS imagedata as described below, the HTS optical module 209 is moved out of theoptical path and the HCS optical module 203 is moved into place.

The optical module for HTS 209 consists of a projection lens 214,excitation wavelength filter 213 and dichroic mirror 210 which are usedto illuminate the whole bottom of the plate with a specific wavelengthband from a conventional microscope lamp system (not illustrated). Thefluorescence emission is collected through the dichroic mirror 210 andemission wavelength filter 211 by a lens 212 which forms an image on thecamera 216 with sensor 215.

The optical module for HCS 203 consists of a projection lens 208,excitation wavelength filter 207 and dichroic mirror 204 which are usedto illuminate the back aperture of the microscope objective 202, andthereby the field of that objective, from a standard microscopeillumination system (not shown). The fluorescence emission is collectedby the microscope objective 202 passes through the dichroic mirror 204and emission wavelength filter 205 and is focused by a tube lens 206which forms an image on the same camera 216 with sensor 215.

In an alternative embodiment of the present invention, the cellscreening system further comprises a fluid delivery device for use withthe live cell embodiment of the method of cell screening (see below).FIG. 8 exemplifies a fluid delivery device for use with the system ofthe invention. It consists of a bank of 12 syringe pumps 701 driven by asingle motor drive. Each syringe 702 is sized according to the volume tobe delivered to each well, typically between 1 and 100 μL. Each syringeis attached via flexible tubing 703 to a similar bank of connectorswhich accept standard pipette tips 705. The bank of pipette tips areattached to a drive system so they can be lowered and raised relative tothe microtiter plate 706 to deliver fluid to each well. The plate ismounted on an X,Y stage, allowing movement relative to the opticalsystem 707 for data collection purposes. This set-up allows one set ofpipette tips, or even a single pipette tip, to deliver reagent to allthe wells on the plate. The bank of syringe pumps can be used to deliverfluid to 12 wells simultaneously, or to fewer wells by removing some ofthe tips.

In another aspect, the present invention provides a method for analyzingcells comprising providing an array of locations which contain multiplecells wherein the cells contain one or more fluorescent reportermolecules; scanning multiple cells in each of the locations containingcells to obtain fluorescent signals from the fluorescent reportermolecule in the cells; converting the fluorescent signals into digitaldata; and utilizing the digital data to determine the distribution,environment or activity of the fluorescent reporter molecule within thecells.

Cell Arrays

Screening large numbers of compounds for activity with respect to aparticular biological function requires preparing arrays of cells forparallel handling of cells and reagents. Standard 96 well microtiterplates which are 86 mm by 129 mm, with 6 mm diameter wells on a 9 mmpitch, are used for compatibility with current automated loading androbotic handling systems. The microplate is typically 20 mm by 30 mm,with cell locations that are 100-200 microns in dimension on a pitch ofabout 500 microns. Methods for making microplates are described in U.S.patent application Ser. No. 08/865,341, incorporated by reference hereinin its entirety. Microplates may consist of coplanar layers of materialsto which cells adhere, patterned with materials to which cells will notadhere, or etched 3-dimensional surfaces of similarly patteredmaterials. For the purpose of the following discussion, the terms ‘well’and ‘microwell’ refer to a location in an array of any construction towhich cells adhere and within which the cells are imaged. Microplatesmay also include fluid delivery channels in the spaces between thewells. The smaller format of a microplate increases the overallefficiency of the system by minimizing the quantities of the reagents,storage and handling during preparation and the overall movementrequired for the scanning operation. In addition, the whole area of themicroplate can be imaged more efficiently, allowing a second mode ofoperation for the microplate reader as described later in this document.

Fluorescence Reporter Molecules

A major component of the new drug discovery paradigm is a continuallygrowing family of fluorescent and luminescent reagents that are used tomeasure the temporal and spatial distribution, content, and activity ofintracellular ions, metabolites, macromolecules, and organelles. Classesof these reagents include labeling reagents that measure thedistribution and amount of molecules in living and fixed cells,environmental indicators to report signal transduction events in timeand space, and fluorescent protein biosensors to measure targetmolecular activities within living cells. A multiparameter approach thatcombines several reagents in a single cell is a powerful new tool fordrug discovery.

The method of the present invention is based on the high affinity offluorescent or luminescent molecules for specific cellular components.The affinity for specific components is governed by physical forces suchas ionic interactions, covalent bonding (which includes chimeric fusionwith protein-based chromophores, fluorophores, and lumiphores), as wellas hydrophobic interactions, electrical potential, and, in some cases,simple entrapment within a cellular component. The luminescent probescan be small molecules, labeled macromolecules, or geneticallyengineered proteins, including, but not limited to green fluorescentprotein chimeras.

Those skilled in this art will recognize a wide variety of fluorescentreporter molecules that can be used in the present invention, including,but not limited to, fluorescently labeled biomolecules such as proteins,phospholipids and DNA hybridizing probes. Similarly, fluorescentreagents specifically synthesized with particular chemical properties ofbinding or association have been used as fluorescent reporter molecules(Barak et al., (1997), J. Biol. Chem. 272:27497-27500; Southwick et al.,(1990), Cytometry 11:418-430; Tsien (1989) in Methods in Cell Biology,Vol. 29 Taylor and Wang (eds.), pp. 127-156). Fluorescently labeledantibodies are particularly useful reporter molecules due to their highdegree of specificity for attaching to a single molecular target in amixture of molecules as complex as a cell or tissue.

The luminescent probes can be synthesized within the living cell or canbe transported into the cell via several non-mechanical modes includingdiffusion, facilitated or active transport, signal-sequence-mediatedtransport, and endocytotic or pinocytotic uptake. Mechanical bulkloading methods, which are well known in the art, can also be used toload luminescent probes into living cells (Barber et al. (1996),Neuroscience Letters 207:17-20; Bright et al. (1996), Cytometry24:226-233; McNeil (1989) in Methods in Cell Biology, Vol. 29, Taylorand Wang (eds.), pp. 153-173). These methods include electroporation andother mechanical methods such as scrape-loading, bead-loading,impact-loading, syringe-loading, hypertonic and hypotonic loading.Additionally, cells can be genetically engineered to express reportermolecules, such as GFP, coupled to a protein of interest as previouslydescribed (Chalfie and Prasher U.S. Pat. No. 5,491,084; Cubitt et al.(1995), Trends in Biochemical Science 20:448-455).

Once in the cell, the luminescent probes accumulate at their targetdomain as a result of specific and high affinity interactions with thetarget domain or other modes of molecular targeting such assignal-sequence-mediated transport. Fluorescently labeled reportermolecules are useful for determining the location, amount and chemicalenvironment of the reporter. For example, whether the reporter is in alipophilic membrane environment or in a more aqueous environment can bedetermined (Giuliano et al. (1995), Ann. Rev. of Biophysics andBiomolecular Structure 24:405-434; Giuliano and Taylor (1995), Methodsin Neuroscience 27:1-16). The pH environment of the reporter can bedetermined (Bright et al. (1989), J. Cell Biology 104:1019-1033;Giuliano et al. (1987), Anal. Biochem. 167:362-371; Thomas et al.(1979), Biochemistry 18:2210-2218). It can be determined whether areporter having a chelating group is bound to an ion, such as Ca++, ornot (Bright et al. (1989), In Methods in Cell Biology, Vol. 30, Taylorand Wang (eds.), pp. 157-192; Shimoura et al. (1988), J. of Biochemistry(Tokyo) 251:405-410; Tsien (1989) In Methods in Cell Biology, Vol. 30,Taylor and Wang (eds.), pp. 127-156).

Furthermore, certain cell types within an organism may containcomponents that can be specifically labeled that may not occur in othercell types. For example, epithelial cells often contain polarizedmembrane components. That is, these cells asymmetrically distributemacromolecules along their plasma membrane. Connective or supportingtissue cells often contain granules in which are trapped moleculesspecific to that cell type (e.g., heparin, histamine, serotonin, etc.).Most muscular tissue cells contain a sarcoplasmic reticulum, aspecialized organelle whose function is to regulate the concentration ofcalcium ions within the cell cytoplasm. Many nervous tissue cellscontain secretory granules and vesicles in which are trappedneurohormones or neurotransmitters. Therefore, fluorescent molecules canbe designed to label not only specific components within specific cells,but also specific cells within a population of mixed cell types.

Those skilled in the art will recognize a wide variety of ways tomeasure fluorescence. For example, some fluorescent reporter moleculesexhibit a change in excitation or emission spectra, some exhibitresonance energy transfer where one fluorescent reporter losesfluorescence, while a second gains in fluorescence, some exhibit a loss(quenching) or appearance of fluorescence, while some report rotationalmovements (Giuliano et al. (1995), Ann. Rev. of Biophysics and Biomol.Structure 24:405-434; Giuliano et al. (1995), Methods in Neuroscience27:1-16).

Scanning Cell Arrays

Referring to FIG. 9, a preferred embodiment is provided to analyze cellsthat comprises operator-directed parameters being selected based on theassay being conducted, data acquisition by the cell screening system onthe distribution of fluorescent signals within a sample, and interactivedata review and analysis. At the start of an automated scan the operatorenters information 100 that describes the sample, specifies the filtersettings and fluorescent channels to match the biological labels beingused and the information sought, and then adjusts the camera settings tomatch the sample brightness. For flexibility to handle a range ofsamples, the software allows selection of various parameter settingsused to identify nuclei and cytoplasm, and selection of differentfluorescent reagents, identification of cells of interest based onmorphology or brightness, and cell numbers to be analyzed per well.These parameters are stored in the system's for easy retrieval for eachautomated run. The system's interactive cell identification modesimplifies the selection of morphological parameter limits such as therange of size, shape, and intensity of cells to be analyzed. The userspecifies which wells of the plate the system will scan and how manyfields or how many cells to analyze in each well. Depending on the setupmode selected by the user at step 101, the system either automaticallypre-focuses the region of the plate to be scanned using an autofocusprocedure to “find focus” of the plate 102 or the user interactivelypre-focuses 103 the scanning region by selecting three “tag” pointswhich define the rectangular area to be scanned. A least-squares fit“focal plane model” is then calculated from these tag points to estimatethe focus of each well during an automated scan. The focus of each wellis estimated by interpolating from the focal plane model during a scan.

During an automated scan, the software dynamically displays the scanstatus, including the number of cells analyzed, the current well beinganalyzed, images of each independent wavelength as they are acquired,and the result of the screen for each well as it is determined. Theplate 4 (FIG. 1) is scanned in a serpentine style as the softwareautomatically moves the motorized microscope XY stage 3 from well towell and field to field within each well of a 96-well plate. Thoseskilled in the programming art will recognize how to adapt software forscanning of other microplate formats such as 24, 48, and 384 wellplates. The scan pattern of the entire plate as well as the scan patternof fields within each well are programmed. The system adjusts samplefocus with an autofocus procedure 104 (FIG. 9) through the Z axis focusdrive 5, controls filter selection via a motorized filter wheel 19 andacquires and analyzes images of up to four different colors (“channels”or “wavelengths”).

The autofocus procedure is called at a user selected frequency,typically for the first field in each well and then once every 4 to 5fields within each well. The autofocus procedure calculates the startingZ-axis point by interpolating from the pre-calculated plane focal model.Starting a programmable distance above or below this set point, theprocedure moves the mechanical Z-axis through a number of differentpositions, acquires an image at each position, and finds the maximum ofa calculated focus score that estimates the contrast of each image. TheZ position of the image with the maximum focus score determines the bestfocus for a particular field. Those skilled in the art will recognizethis as a variant of automatic focusing methods as described in Harms etal. in Cytometry 5 (1984), 236-243, Groen et al. in Cytometry 6 (1985),81-91, and Firestone et al. in Cytometry 12 (1991), 195-206.

For image acquisition, the camera's exposure time is separately adjustedfor each dye to ensure a high-quality image from each channel. Softwareprocedures can be called, at the user's option, to correct forregistration shifts between wavelengths by accounting for linear (X andY) shifts between wavelengths before making any further measurements.The electronic shutter 18 is controlled so that sample photo-bleachingis kept to a minimum. Background shading and uneven illumination can becorrected by the software using methods known in the art (Bright et al.(1987), J. Cell Biol. 104:1019-1033).

In one channel, images are acquired of a primary marker 105 (FIG. 9)(typically cell nuclei counterstained with DAPI or PI fluorescent dyes)which are segmented (“identified”) using an adaptive thresholdingprocedure. The adaptive thresholding procedure 106 is used todynamically select the threshold of an image for separating cells fromthe background. The staining of cells with fluorescent dyes can vary toan unknown degree across cells in a microtiter plate sample as well aswithin images of a field of cells within each well of a microtiterplate. This variation can occur as a result of sample preparation and/orthe dynamic nature of cells. A global threshold is calculated for thecomplete image to separate the cells from background and account forfield to field variation. These global adaptive techniques are variantsof those described in the art. (Kittler et al. in Computer Vision,Graphics, and Image Processing 30 (1985), 125-147, Ridler et al. in IEEETrans. Systems, Man, and Cybernetics (1978), 630-632.)

An alternative adaptive thresholding method utilizes local regionthresholding in contrast to global image thresholding. Image analysis oflocal regions leads to better overall segmentation since staining ofcell nuclei (as well as other labeled components) can vary across animage. Using this global/local procedure, a reduced resolution image(reduced in size by a factor of 2 to 4) is first globally segmented(using adaptive thresholding) to find regions of interest in the image.These regions then serve as guides to more fully analyze the sameregions at full resolution. A more localized threshold is thencalculated (again using adaptive thresholding) for each region ofinterest.

The output of the segmentation procedure is a binary image wherein theobjects are white and the background is black. This binary image, alsocalled a mask in the art, is used to determine if the field containsobjects 107. The mask is labeled with a blob labeling method wherebyeach object (or blob) has a unique number assigned to it. Morphologicalfeatures, such as area and shape, of the blobs are used to differentiateblobs likely to be cells from those that are considered artifacts. Theuser pre-sets the morphological selection criteria by either typing inknown cell morphological features or by using the interactive trainingutility. If objects of interest are found in the field, images areacquired for all other active channels 108 otherwise the stage isadvanced to the next field 109 in the current well. Each object ofinterest is located in the image for further analysis 110. The softwaredetermines if the object meets the criteria for a valid cell nucleus 111by measuring its morphological features (size and shape). For each validcell, the XYZ stage location is recorded, a small image of the cell isstored, and features are measured 112.

The cell scanning method of the present invention can be used to performmany different assays on cellular samples by applying a number ofanalytical methods simultaneously to measure features at multiplewavelengths. An example of one such assay provides for the followingmeasurements:

-   -   1. The total fluorescent intensity within the cell nucleus for        colors 1-4    -   2. The area of the cell nucleus for color 1 (the primary marker)    -   3. The shape of the cell nucleus for color 1 is described by        three shape features:        -   a) perimeter squared area        -   b) box area ratio        -   c) height width ratio    -   4. The average fluorescent intensity within the cell nucleus for        colors 1-4 (i.e. #1 divided by #2)    -   5. The total fluorescent intensity of a ring outside the nucleus        (see FIG. 10) that represents fluorescence of the cell's        cytoplasm (cytoplasmic mask) for colors 2-4    -   6. The area of the cytoplasmic mask    -   7. The average fluorescent intensity of the cytoplasmic mask for        colors 2-4 (i.e. #5 divided by #6)    -   8. The ratio of the average fluorescent intensity of the        cytoplasmic mask to average fluorescent intensity within the        cell nucleus for colors 2-4 (i.e. #7 divided by #4)    -   9. The difference of the average fluorescent intensity of the        cytoplasmic mask and the average fluorescent intensity within        the cell nucleus for colors 2-4 (i.e. #7 minus #4)    -   10. The number of fluorescent domains (also call spots, dots, or        grains) within the cell nucleus for colors 2-4

Features 1 through 4 are general features of the different cellscreening assays of the invention. These steps are commonly used in avariety of image analysis applications and are well known in art (Russ(1992) The Image Processing Handbook, CRC Press Inc.; Gonzales et al.(1987), Digital Image Processing. Addison-Wesley Publishing Co. pp.391-448). Features 5-9 have been developed specifically to providemeasurements of a cell's fluorescent molecules within the localcytoplasmic region of the cell and the translocation (i.e. movement) offluorescent molecules from the cytoplasm to the nucleus. These features(steps 5-9) are used for analyzing cells in microplates for theinhibition of nuclear translocation. For example, inhibition of nucleartranslocation of transcription factors provides a novel approach toscreening intact cells (detailed examples of other types of screens willbe provided below). A specific method measures the amount of probe inthe nuclear region (feature 4) versus the local cytoplasmic region(feature 7) of each cell. Quantification of the difference between thesetwo sub-cellular compartments provides a measure of cytoplasm-nucleartranslocation (feature 9).

Feature 10 describes a screen used for counting of DNA or RNA probeswithin the nuclear region in colors 2-4. For example, probes arecommercially available for identifying chromosome-specific DNA sequences(Life Technologies, Gaithersburg, Md.; Genosys, Woodlands, Tex.;Biotechnologies, Inc., Richmond, Calif.; Bio 101, Inc., Vista, Calif.)Cells are three-dimensional in nature and when examined at a highmagnification under a microscope one probe may be in-focus while anothermay be completely out-of-focus. The cell screening method of the presentinvention provides for detecting three-dimensional probes in nuclei byacquiring images from multiple focal planes. The software moves theZ-axis motor drive 5 (FIG. 1) in small steps where the step distance isuser selected to account for a wide range of different nucleardiameters. At each of the focal steps, an image is acquired. The maximumgray-level intensity from each pixel in each image is found and storedin a resulting maximum projection image. The maximum projection image isthen used to count the probes. The above method works well in countingprobes that are not stacked directly above or below another one. Toaccount for probes stacked on top of each other in the Z-direction,users can select an option to analyze probes in each of the focal planesacquired. In this mode, the scanning system performs the maximum planeprojection method as discussed above, detects probe regions of interestin this image, then further analyzes these regions in all the focalplane images.

After measuring cell features 112 (FIG. 9), the system checks if thereare any unprocessed objects in the current field 113. If there are anyunprocessed objects, it locates the next object 110 and determineswhether it meets the criteria for a valid cell nucleus 111, and measuresits features. Once all the objects in the current field are processed,the system determines whether analysis of the current plate is complete114; if not, it determines the need to find more cells in the currentwell 115. If the need exists, the system advances the XYZ stage to thenext field within the current well 109 or advances the stage to the nextwell 116 of the plate.

After a plate scan is complete, images and data can be reviewed with thesystem's image review, data review, and summary review facilities. Allimages, data, and settings from a scan are archived in the system'sdatabase for later review or for interfacing with a network informationmanagement system. Data can also be exported to other third-partystatistical packages to tabulate results and generate other reports.Users can review the images alone of every cell analyzed by the systemwith an interactive image review procedure 117. The user can review dataon a cell-by-cell basis using a combination of interactive graphs, adata spreadsheet of measured features, and images of all thefluorescence channels of a cell of interest with the interactivecell-by-cell data review procedure 118. Graphical plotting capabilitiesare provided in which data can be analyzed via interactive graphs suchas histograms and scatter plots. Users can review summary data that areaccumulated and summarized for all cells within each well of a platewith an interactive well-by-well data review procedure 119. Hard copiesof graphs and images can be printed on a wide range of standardprinters.

As a final phase of a complete scan, reports can be generated on one ormore statistics of the measured features. Users can generate a graphicalreport of data summarized on a well-by-well basis for the scanned regionof the plate using an interactive report generation procedure 120. Thisreport includes a summary of the statistics by well in tabular andgraphical format and identification information on the sample. Thereport window allows the operator to enter comments about the scan forlater retrieval. Multiple reports can be generated on many statisticsand be printed with the touch of one button. Reports can be previewedfor placement and data before being printed.

The above-recited embodiment of the method operates in a single highresolution mode referred to as the high content screening (HCS) mode.The HCS mode provides sufficient spatial resolution within a well (onthe order of 1 μm) to define the distribution of material within thewell, as well as within individual cells in the well. The high degree ofinformation content accessible in that mode, comes at the expense ofspeed and complexity of the required signal processing.

In an alternative embodiment, a high throughput system (HTS) is directlycoupled with the HCS either on the same platform or on two separateplatforms connected electronically (e.g. via a local area network). Thisembodiment of the invention, referred to as a dual mode optical system,has the advantage of increasing the throughput of an HCS by coupling itwith an HTS and thereby requiring slower high resolution dataacquisition and analysis only on the small subset of wells that show aresponse in the coupled HTS.

High throughput ‘whole plate’ reader systems are well known in the artand are commonly used as a component of an HTS system used to screenlarge numbers of compounds (Beggs et al. (1997), supra; McCaffrey et al.(1996), supra). The HTS of the present invention is carried out on themicrotiter plate or microwell array by reading many or all wells in theplate simultaneously with sufficient resolution to make determinationson a well-by-well basis. That is, calculations are made by averaging thetotal signal output of many or all the cells or the bulk of the materialin each well. Wells that exhibit some defined response in the HTS (the‘hits’) are flagged by the system. Then on the same microtiter plate ormicrowell array, each well identified as a hit is measured via HCS asdescribed above. Thus, the dual mode process involves:

-   1. Rapidly measuring numerous wells of a microtiter plate or    microwell array,-   2. Interpreting the data to determine the overall activity of    fluorescently labeled reporter molecules in the cells on a    well-by-well basis to identify “hits” (wells that exhibit a defined    response),-   3. Imaging numerous cells in each “hit” well, and-   4. Interpreting the digital image data to determine the    distribution, environment or activity of the fluorescently labeled    reporter molecules in the individual cells (i.e. intracellular    measurements) and the distribution of the cells to test for specific    biological functions

In a preferred embodiment of dual mode processing (FIG. 11), at thestart of a run 301, the operator enters information 302 that describesthe plate and its contents, specifies the filter settings andfluorescent channels to match the biological labels being used, theinformation sought and the camera settings to match the samplebrightness. These parameters are stored in the system's database foreasy retrieval for each automated run. The microtiter plate or microwellarray is loaded into the cell screening system 303 either manually orautomatically by controlling a robotic loading device. An optionalenvironmental chamber 304 is controlled by the system to maintain thetemperature, humidity and CO₂ levels in the air surrounding live cellsin the microtiter plate or microwell array. An optional fluid deliverydevice 305 (see FIG. 8) is controlled by the system to dispense fluidsinto the wells during the scan.

High throughput processing 306 is first performed on the microtiterplate or microwell array by acquiring and analyzing the signal from eachof the wells in the plate. The processing performed in high throughputmode 307 is illustrated in FIG. 12 and described below. Wells thatexhibit some selected intensity response in this high throughput mode(“hits”) are identified by the system. The system performs a conditionaloperation 308 that tests for hits. If hits are found, those specific hitwells are further analyzed in high content (micro level) mode 309. Theprocessing performed in high content mode 312 is illustrated in FIG. 13.The system then updates 310 the informatics database 311 with results ofthe measurements on the plate. If there are more plates to be analyzed313 the system loads the next plate 303; otherwise the analysis of theplates terminates 314.

The following discussion describes the high throughput mode illustratedin FIG. 12. The preferred embodiment of the system, the single platformdual mode screening system, will be described. Those skilled in the artwill recognize that operationally the dual platform system simplyinvolves moving the plate between two optical systems rather than movingthe optics. Once the system has been set up and the plate loaded, thesystem begins the HTS acquisition and analysis 401. The HTS opticalmodule is selected by controlling a motorized optical positioning device402 on the dual mode system. In one fluorescence channel, data from aprimary marker on the plate is acquired 403 and wells are isolated fromthe plate background using a masking procedure 404. Images are alsoacquired in other fluorescence channels being used 405. The region ineach image corresponding to each well 406 is measured 407. A featurecalculated from the measurements for a particular well is compared witha predefined threshold or intensity response 408, and based on theresult the well is either flagged as a “hit” 409 or not. The locationsof the wells flagged as hits are recorded for subsequent high contentmode processing. If there are wells remaining to be processed 410 theprogram loops back 406 until all the wells have been processed 411 andthe system exits high throughput mode.

Following HTS analysis, the system starts the high content modeprocessing 501 defined in FIG. 13. The system selects the HCS opticalmodule 502 by controlling the motorized positioning system. For each“hit” well identified in high throughput mode, the XY stage location ofthe well is retrieved from memory or disk and the stage is then moved tothe selected stage location 503. The autofocus procedure 504 is calledfor the first field in each hit well and then once every 5 to 8 fieldswithin each well. In one channel, images are acquired of the primarymarker 505 (typically cell nuclei counterstained with DAPI, Hoechst orPI fluorescent dye). The images are then segmented (separated intoregions of nuclei and non-nuclei) using an adaptive thresholdingprocedure 506. The output of the segmentation procedure is a binary maskwherein the objects are white and the background is black. This binaryimage, also called a mask in the art, is used to determine if the fieldcontains objects 507. The mask is labeled with a blob labeling methodwhereby each object (or blob) has a unique number assigned to it. Ifobjects are found in the field, images are acquired for all other activechannels 508, otherwise the stage is advanced to the next field 514 inthe current well. Each object is located in the image for furtheranalysis 509. Morphological features, such as area and shape of theobjects, are used to select objects likely to be cell nuclei 510, anddiscard (do no further processing on) those that are consideredartifacts. For each valid cell nucleus, the XYZ stage location isrecorded, a small image of the cell is stored, and assay specificfeatures are measured 511. The system then performs multiple tests onthe cells by applying several analytical methods to measure features ateach of several wavelengths. After measuring the cell features, thesystems checks if there are any unprocessed objects in the current field512. If there are any unprocessed objects, it locates the next object509 and determines whether it meets the criteria for a valid cellnucleus 510 and measures its features. After processing all the objectsin the current field, the system deteremines whether it needs to findmore cells or fields in the current well 513. If it needs to find morecells or fields in the current well it advances the XYZ stage to thenext field within the current well 515. Otherwise, the system checkswhether it has any remaining hit wells to measure 515. If so, itadvances to the next hit well 503 and proceeds through another cycle ofacquisition and analysis, otherwise the HCS mode is finished 516.

In an alternative embodiment of the present invention, a method ofkinetic live cell screening is provided. The previously describedembodiments of the invention are used to characterize the spatialdistribution of cellular components at a specific point in time, thetime of chemical fixation. As such, these embodiments have limitedutility for implementing kinetic based screens, due to the sequentialnature of the image acquisition, and the amount of time required to readall the wells on a plate. For example, since a plate can require 30-60minutes to read through all the wells, only very slow kinetic processescan be measured by simply preparing a plate of live cells and thenreading through all the wells more than once. Faster kinetic processescan be measured by taking multiple readings of each well beforeproceeding to the next well, but the elapsed time between the first andlast well would be too long, and fast kinetic processes would likely becomplete before reaching the last well.

The kinetic live cell extension of the invention enables the design anduse of screens in which a biological process is characterized by itskinetics instead of, or in addition to, its spatial characteristics. Inmany cases, a response in live cells can be measured by adding a reagentto a specific well and making multiple measurements on that well withthe appropriate timing. This dynamic live cell embodiment of theinvention therefore includes apparatus for fluid delivery to individualwells of the system in order to deliver reagents to each well at aspecific time in advance of reading the well. This embodiment therebyallows kinetic measurements to be made with temporal resolution ofseconds to minutes on each well of the plate. To improve the overallefficiency of the dynamic live cell system, the acquisition controlprogram is modified to allow repetitive data collection from sub-regionsof the plate, allowing the system to read other wells between the timepoints required for an individual well.

FIG. 8 describes an example of a fluid delivery device for use with thelive cell embodiment of the invention and is described above. Thisset-up allows one set of pipette tips 705 or even a single pipette tip,to deliver reagent to all the wells on the plate. The bank of syringepumps 701 can be used to deliver fluid to 12 wells simultaneously, or tofewer wells by removing some of the tips 705. The temporal resolution ofthe system can therefore be adjusted, without sacrificing datacollection efficiency, by changing the number of tips and the scanpattern as follows. Typically, the data collection and analysis from asingle well takes about 5 seconds. Moving from well to well and focusingin a well requires about 5 seconds, so the overall cycle time for a wellis about 10 seconds. Therefore, if a single pipette tip is used todeliver fluid to a single well, and data is collected repetitively fromthat well, measurements can be made with about 5 seconds temporalresolution. If 6 pipette tips are used to deliver fluids to 6 wellssimultaneously, and the system repetitively scans all 6 wells, each scanwill require 60 seconds, thereby establishing the temporal resolution.For slower processes which only require data collection every 8 minutes,fluids can be delivered to one half of the plate, by moving the plateduring the fluid delivery phase, and then repetitively scanning thathalf of the plate. Therefore, by adjusting the size of the sub-regionbeing scanned on the plate, the temporal resolution can be adjustedwithout having to insert wait times between acquisitions. Because thesystem is continuously scanning and acquiring data, the overall time tocollect a kinetic data set from the plate is then simply the time toperform a single scan of the plate, multiplied by the number of timepoints required. Typically, 1 time point before addition of compoundsand 2 or 3 time points following addition should be sufficient forscreening purposes.

FIG. 14 shows the acquisition sequence used for kinetic analysis. Thestart of processing 801 is configuration of the system, much of which isidentical to the standard HCS configuration. In addition, the operatormust enter information specific to the kinetic analysis being performed802, such as the sub-region size, the number of time points required,and the required time increment. A sub-region is a group of wells thatwill be scanned repetitively in order to accumulate kinetic data. Thesize of the sub-region is adjusted so that the system can scan a wholesub-region once during a single time increment, thus minimizing waittimes. The optimum sub-region size is calculated from the setupparameters, and adjusted if necessary by the operator. The system thenmoves the plate to the first sub-region 803, and to the first well inthat sub-region 804 to acquire the prestimulation (time=0) time points.The acquisition sequence per-formed in each well is exactly the same asthat required for the specific HCS being run in kinetic mode. FIG. 15details a flow chart for that processing. All of the steps between thestart 901 and the return 902 are identical to those described as steps504-514 in FIG. 13.

After processing each well in a sub-region, the system checks to see ifall the wells in the sub-region have been processed 806 (FIG. 14), andcycles through all the wells until the whole region has been processed.The system then moves the plate into position for fluid addition, andcontrols fluidic system delivery of fluids to the entire sub-region 807.This may require multiple additions for sub-regions which span severalrows on the plate, with the system moving the plate on the XY stagebetween additions. Once the fluids have been added, the system moves tothe first well in the sub-region 808 to begin acquisition of timepoints. The data is acquired from each well 809 and as before the systemcycles through all the wells in the sub-region 810. After each passthrough the sub-region, the system checks whether all the time pointshave been collected 811 and if not, pauses 813 if necessary 812 to staysynchronized with the requested time increment. Otherwise, the systemchecks for additional sub-regions on the plate 814 and either moves tothe next sub-region 803 or finishes 815. Thus, the kinetic analysis modecomprises operator identification of sub-regions of the microtiter plateor microwells to be screened, based on the kinetic response to beinvestigated, with data acquisitions within a sub-region prior to dataacquisition in subsequent sub-regions.

Specific Screens

In another aspect of the present invention, cell screening methods andmachine readable storage medium comprising a program containing a set ofinstructions for causing a cell screening system to execute proceduresfor defining the distribution and activity of specific cellularconstituents and processes is provided. In a preferred embodiment, thecell screening system comprises a high magnification fluorescenceoptical system with a stage adapted for holding cells and a means formoving the stage, a digital camera, a light source for receiving andprocessing the digital data from the digital camera, and a computermeans for receiving and processing the digital data from the digitalcamera. This aspect of the invention comprises programs that instructthe cell screening system to define the distribution and activity ofspecific cellular constituents and processes, using the luminescentprobes, the optical imaging system, and the pattern recognition softwareof the invention. Preferred embodiments of the machine readable storagemedium comprise programs consisting of a set of instructions for causinga cell screening system to execute the procedures set forth in FIGS. 9,11, 12, 13, 14 or 15. Another preferred embodiment comprises a programconsisting of a set of instructions for causing a cell screening systemto execute procedures for detecting the distribution and activity ofspecific cellular constituents and processes. In most preferredembodiments, the cellular processes include, but are not limited to,nuclear translocation of a protein, cellular morphology, apoptosis,receptor internalization, and protease-induced translocation of aprotein.

In a preferred embodiment, the cell screening methods are used toidentify compounds that modify the various cellular processes. The cellscan be contacted with a test compound, and the effect of the testcompound on a particular cellular process can be analyzed.Alternatively, the cells can be contacted with a test compound and aknown agent that modifies the particular cellular process, to determinewhether the test compound can inhibit or enhance the effect of the knownagent. Thus, the methods can be used to identify test compounds thatincrease or decrease a particular cellular response, as well as toidentify test compounds that affects the ability of other agents toincrease or decrease a particular cellular response.

In another preferred embodiment, the locations containing cells areanalyzed using the above methods at low resolution in a high throughputmode, and only a subset of the locations containing cells are analyzedin a high content mode to obtain luminescent signals from theluminescently labeled reporter molecules in subcellular compartments ofthe cells being analyzed.

The following examples are intended for purposes of illustration onlyand should not be construed to limit the scope of the invention, asdefined in the claims appended hereto.

The various chemical compounds, reagents, dyes, and antibodies that arereferred to in the following Examples are commercially available fromsuch sources as Sigma Chemical (St. Louis, Mo.), Molecular Probes(Eugene, Oreg.), Aldrich Chemical Company (Milwaukee, Wis.), AccurateChemical Company (Westbury, N.Y.), Jackson Immunolabs, and Clontech(Palo Alto, Calif.).

EXAMPLE 1 Cytoplasm to Nucleus Translocation Screening

a. Transcription Factors

Regulation of transcription of some genes involves activation of atranscription factor in the cytoplasm, resulting in that factor beingtransported into the nucleus where it can initiate transcription of aparticular gene or genes. This change in transcription factordistribution is the basis of a screen for the cell-based screeningsystem to detect compounds that inhibit or induce transcription of aparticular gene or group of genes. A general description of the screenis given followed by a specific example.

The distribution of the transcription factor is determined by labelingthe nuclei with a DNA specific fluorophore like Hoechst 33423 and thetranscription factor with a specific fluorescent antibody. Afterautofocusing on the Hoechst labeled nuclei, an image of the nuclei isacquired in the cell-based screening system and used to create a mask byone of several optional thresholding methods, as described supra. Themorphological descriptors of the regions defined by the mask arecompared with the user defined parameters and valid nuclear masks areidentified and used with the following method to extract transcriptionfactor distributions. Each valid nuclear mask is eroded to define aslightly smaller nuclear region. The original nuclear mask is thendilated in two steps to define a ring shaped region around the nucleus,which represents a cytoplasmic region. The average antibody fluorescencein each of these two regions is determined, and the difference betweenthese averages is defined as the NucCyt Difference. Two examples ofdetermining nuclear translocation are discussed below and illustrated inFIG. 10A-J. FIG. 10A illustrates an unstimulated cell with its nucleus200 labeled with a blue fluorophore and a transcription factor in thecytoplasm 201 labeled with a green fluorophore. FIG. 10B illustrates thenuclear mask 202 derived by the cell-based screening system. FIG. 10Cillustrates the cytoplasm 203 of the unstimulated cell imaged at a greenwavelength. FIG. 10D illustrates the nuclear mask 202 is eroded(reduced) once to define a nuclear sampling region 204 with minimalcytoplasmic distribution. The nucleus boundary 202 is dilated (expanded)several times to form a ring that is 2-3 pixels wide that is used todefine the cytoplasmic sampling region 205 for the same cell. FIG. 10Efurther illustrates a side view which shows the nuclear sampling region204 and the cytoplasmic sampling region 205. Using these two samplingregions, data on nuclear translocation can be automatically analyzed bythe cell-based screening system on a cell by cell basis. FIG. 10F-Jillustrates the strategy for determining nuclear translocation in astimulated cell. FIG. 10F illustrates a stimulated cell with its nucleus206 labeled with a blue fluorophore and a transcription factor in thecytoplasm 207 labeled with a green fluorophore. The nuclear mask 208 inFIG. 10G is derived by the cell based screening system. FIG. 10Hillustrates the cytoplasm 209 of a stimulated cell imaged at a greenwavelength. FIG. 101 illustrates the nuclear sampling region 211 andcytoplasmic sampling region 212 of the stimulated cell. FIG. 10J furtherillustrates a side view which shows the nuclear sampling region 211 andthe cytoplasmic sampling region 212.

A specific application of this method has been used to validate thismethod as a screen. A human cell line was plated in 96 well microtiterplates. Some rows of wells were titrated with IL-1, a known inducer ofthe NF-KB transcription factor. The cells were then fixed and stained bystandard methods with a fluorescein labeled antibody to thetranscription factor, and Hoechst 33423. The cell-based screening systemwas used to acquire and analyze images from this plate and the NucCytDifference was found to be strongly correlated with the amount ofagonist added to the wells as illustrated in FIG. 16. In a secondexperiment, an antagonist to the receptor for IL-1, IL-1RA was titratedin the presence of IL-1α, progressively inhibiting the translocationinduced by IL-1α. The NucCyt Difference was found to strongly correlatewith this inhibition of translocation, as illustrated in FIG. 17.

Additional experiments have shown that the NucCyt Difference, as well asthe NucCyt ratio, gives consistent results over a wide range of celldensities and reagent concentrations, and can therefore be routinelyused to screen compound libraries for specific nuclear translocationactivity. Furthermore, the same method can be used with antibodies toother transcription factors, or GFP-transcription factor chimeras, orfluorescently labeled transcription factors introduced into living orfixed cells, to screen for effects on the regulation of transcriptionfactor activity.

FIG. 18 is a representative display on a PC screen of data which wasobtained in accordance with Example 1. Graph 1 180 plots the differencebetween the average antibody fluorescence in the nuclear sampling regionand cytoplasmic sampling region, NucCyt Difference verses Well #. Graph2 181 plots the average fluorescence of the antibody in the nuclearsampling region, NP1 average, versus the Well #. Graph 3 182 plots theaverage antibody fluorescence in the cytoplasmic sampling region, LIP1average, versus Well #. The software permits displaying data from eachcell. For example, FIG. 18 shows a screen display 183, the nuclear image184, and the fluorescent antibody image 185 for cell #26.

NucCyt Difference referred to in graph 1 180 of FIG. 18 is thedifference between the average cytoplasmic probe (fluorescent reportermolecule) intensity and the average nuclear probe (fluorescent reportermolecule) intensity. NP1 average referred to in graph 2 181 of FIG. 18is the average of cytoplasmic probe (fluorescent reporter molecule)intensity within the nuclear sampling region. L1P1 average referred toin graph 3 182 of FIG. 18 is the average probe (fluorescent reportermolecule) intensity within the cytoplasmic sampling region.

It will be understood by one of skill in the art that this aspect of theinvention can be performed using other transcription factors thattranslocate from the cytoplasm to the nucleus upon activation. Inanother specific example, activation of the c-fos transcription factorwas assessed by defining its spatial position within cells. Activatedc-fos is found only within the nucleus, while inactivated c-fos resideswithin the cytoplasm.

3T3 cells were plated at 5000-10000 cells per well in a Polyfiltronics96-well plate. The cells were allowed to attach and grow overnight. Thecells were rinsed twice with 100 μl serum-free medium, incubated for24-30 hours in serum-free MEM culture medium, and then stimulated withplatelet derived growth factor (PDGF-BB) (Sigma Chemical Co., St. Louis,Mo.) diluted directly into serum free medium at concentrations rangingfrom 1-50 ng/ml for an average time of 20 minutes.

Following stimulation, cells were fixed for 20 minutes in 3.7%formaldehyde solution in 1× Hanks buffered saline solution (HBSS). Afterfixation, the cells were washed with HBSS to remove residual fixative,permeabilized for 90 seconds with 0.5% Triton X-100 solution in HBSS,and washed twice with HBSS to remove residual detergent. The cells werethen blocked for 15 minutes with a 0.1% solution of BSA in HBSS, andfurther washed with HBSS prior to addition of diluted primary antibodysolution.

c-Fos rabbit polyclonal antibody (Calbiochem, PC05) was diluted 1:50 inHBSS, and 50 μl of the dilution was applied to each well. Cells wereincubated in the presence of primary antibody for one hour at roomtemperature, and then incubated for one hour at room temperature in alight tight container with goat anti-rabbit secondary antibodyconjugated to ALEXA™ 488 (Molecular Probes), diluted 1:500 from a 100μg/ml stock in HBSS. Hoechst DNA dye (Molecular Probes) was then addedat a 1:1000 dilution of the manufacturer's stock solution (10 mg/ml).The cells were then washed with HBSS, and the plate was sealed prior toanalysis with the cell screening system of the invention. The data fromthese experiments demonstrated that the methods of the invention couldbe used to measure transcriptional activation of c-fos by defining itsspatial position within cells.

One of skill in the art will recognize that while the following methodis applied to detection of c-fos activation, it can be applied to theanalysis of any transcription factor that translocates from thecytoplasm to the nucleus upon activation. Examples of such transcriptionfactors include, but are not limited to fos and jun homologs, NF-KB(nuclear factor kappa from B cells), NFAT (nuclear factor of activatedT-lymphocytes), and STATs (signal transducer and activator oftranscription) factors (For example, see Strehlow, I., and Schindler, C.1998. J. Biol. Chem. 273:28049-28056; Chow, et al. 1997 Science.278:1638-1641; Ding et al. 1998 J. Biol. Chem. 273:28897-28905; Baldwin,1996. Annu Rev Immunol. 14:649-83; Kuo, C. T., and J. M. Leiden. 1999.Annu Rev Immunol. 17:149-87; Rao, et al. 1997. Annu Rev Immunol.15:707-47; Masuda, et al. 1998. Cell Signal. 10:599-611; Hoey, T., andU. Schindler. 1998. Curr Opin Genet Dev. 8:582-7; Liu, et al. 1998. CurrOpin Immunol. 10:271-8.)

Thus, in this aspect of the invention, indicator cells are treated withtest compounds and the distribution of luminescently labeledtranscription factor is measured in space and time using a cellscreening system, such as the one disclosed above. The luminescentlylabeled transcription factor may be expressed by or added to the cellseither before, together with, or after contacting the cells with a testcompound. For example, the transcription factor may be expressed as aluminescently labeled protein chimera by transfected indicator cells.Alternatively, the luminescently labeled transcription factor may beexpressed, isolated, and bulk-loaded into the indicator cells asdescribed above, or the transcription factor may be luminescentlylabeled after isolation. As a further alternative, the transcriptionfactor is expressed by the indicator cell, which is subsequentlycontacted with a luminescent label, such as an antibody, that detectsthe transcription factor.

In a further aspect, kits are provided for analyzing transcriptionfactor activation, comprising an antibody that specifically recognizes atranscription factor of interest, and instructions for using theantibody for carrying out the methods described above. In a preferredembodiment, the transcription factor-specific antibody, or a secondaryantibody that detects the transcription factor antibody, isluminescently labeled. In further preferred embodiments, the kitcontains cells that express the transcription factor of interest, and/orthe kit contains a compound that is known to modify activation of thetranscription factor of interest, including but not limited to plateletderived growth factor (PDGF) and serum, which both modify fosactivation; and interleukin 1 (IL-1) and tumor necrosis factor (TNF),which both modify NF-KB activation.

In another embodiment, the kit comprises a recombinant expression vectorcomprising a nucleic acid encoding a transcription factor of interestthat translocates from the cytoplasm to the nucleus upon activation, andinstructions for using the expression vector to identify compounds thatmodify transcription factor activation in a cell of interest.Alternatively, the kits contain a purified, luminescently labeledtranscription factor. In a preferred embodiment, the transcriptionfactor is expressed as a fusion protein with a luminescent protein,including but not limited to green fluorescent protein, luceriferase, ormutants or fragments thereof. In various preferred embodiments, the kitfurther contains cells that are transfected with the expression vector,an antibody or fragment that specifically bind to the transcriptionfactor of interest, and/or a compound that is known to modify activationof the transcription factor of interest (as above).

b. Protein Kinases

The cytoplasm to nucleus screening methods can also be used to analyzethe activation of any protein kinase that is present in an inactivestate in the cytoplasm and is transported to the nucleus uponactivation, or that phosphorylates a substrate that translocates fromthe cytoplasm to the nucleus upon phosphorylation. Examples ofappropriate protein kinases include, but are not limited toextracellular signal-regulated protein kinases. (ERKs), c-Junamino-terminal kinases (JNKs), Fos regulating protein kinases (ERKs),p38 mitogen activated protein kinase (p38MAPK), protein kinase A (PKA),and mitogen activated protein kinase kinases (MAPKKs). (For example, seeHall, et al. 1999. J Biol. Chem. 274:376-83; Han, et al. 1995. Biochim.Biophys. Acta. 1265:224-227; Jaaro et al. 1997. Proc. Natl. Acad. Sci.U.S.A. 94:3742-3747; Taylor, et al. 1994. J. Biol. Chem. 269:308-318;Zhao, Q., and F. S. Lee. 1999. J Biol. Chem. 274:8355-8; Paolillo et al.1999. J Biol. Chem. 274:6546-52; Coso et al. 1995. Cell 81:1137-1146;Tibbles, L. A., and J. R. Woodgett. 1999. Cell Mol Life Sci. 55:1230-54;Schaeffer, H. J., and M. J. Weber. 1999. Mol Cell Biol. 19:2435-44.)

Alternatively, protein kinase activity is assayed by monitoringtranslocation of a luminescently labeled protein kinase substrate fromthe cytoplasm to the nucleus after being phosphorylated by the proteinkinase of interest. In this embodiment, the substrate isnon-phosphorylated and cytoplasmic prior to phosphorylation, and istranslocated to the nucleus upon phosphorylation by the protein kinase.There is no requirement that the protein kinase itself translocates fromthe cytoplasm to the nucleus in this embodiment. Examples of suchsubstrates (and the corresponding protein kinase) include, but are notlimited to c-jun (JNK substrate); fos (FRK substrate), and p38 (p38 MAPKsubstrate).

Thus, in these embodiments, indicator cells are treated with testcompounds and the distribution of luminescently labeled protein kinaseor protein kinase substrate is measured in space and time using a cellscreening system, such as the one disclosed above. The luminescentlylabeled protein kinase or protein kinase substrate may be expressed byor added to the cells either before, together with, or after contactingthe cells with a test compound. For example, the protein kinase orprotein kinase substrate may be expressed as a luminescently labeledprotein chimera by transfected indicator cells. Alternatively, theluminescently labeled protein kinase or protein kinase substrate may beexpressed, isolated, and bulk-loaded into the indicator cells asdescribed above, or the protein kinase or protein kinase substrate maybe luminescently labeled after isolation. As a further alternative, theprotein kinase or protein kinase substrate is expressed by the indicatorcell, which is subsequently contacted with a luminescent label, such asa labeled antibody, that detects the protein kinase or protein kinasesubstrate.

In a further embodiment, protein kinase activity is assayed bymonitoring the phosphorylation state (ie: phosphorylated or notphosphorylated) of a protein kinase substrate. In this embodiment, thereis no requirement that either the protein kinase or the protein kinasesubstrate translocate from the cytoplasm to the nucleus upon activation.In a preferred embodiment, phosphorylation state is monitored bycontacting the cells with an antibody that binds only to thephosphorylated form of the protein kinase substrate of interest (Forexample, as disclosed in U.S. Pat. No. 5,599,681).

In another preferred embodiment, a biosensor of phosphorylation is used.For example, a luminescently labeled protein or fragment thereof can befused to a protein that has been engineered to contain (a) aphosphorylation site that is recognized by a protein kinase of interest;and (b) a nuclear localization signal that is unmasked by thephosphorylation. Such a biosensor will thus be translocated to thenucleus upon phosphorylation, and its translocation can be used as ameasure of protein kinase activation.

In another aspect, kits are provided for analyzing protein kinaseactivation, comprising a primary antibody that specifically binds to aprotein kinase, a protein kinase substrate, or a phosphorylated form ofthe protein kinase substrate of interest and instructions for using theprimary antibody to identify compounds that modify protein kinaseactivation in a cell of interest. In a preferred embodiment, the primaryantibody, or a secondary antibody that detects the primary antibody, isluminescently labeled. In other preferred embodiments, the kit furthercomprises cells that express the protein kinase of interest, and/or acompound that is known to modify activation of the protein kinase ofinterest, including but not limited to dibutyryl cAMP (modifies PKA),forskolin (PKA), and anisomycin (p38MAPK).

Alternatively, the kits comprise an expression vector encoding a proteinkinase or a protein kinase substrate of interest that translocates fromthe cytoplasm to the nucleus upon activation and instructions for usingthe expression vector to identify compounds that modify protein kinaseactivation in a cell of interest. Alternatively, the kits contain apurified, luminescently labeled protein kinase or protein kinasesubstrate. In a preferred embodiment, the protein kinase or proteinkinase substrate of interest is expressed as a fusion protein with aluminescent protein. In further preferred embodiments, the kit furthercomprises cells that are transfected with the expression vector, anantibody or fragment thereof that specifically binds to the proteinkinase or protein kinase substrate of interest, and/or a compound thatis known to modify activation of the protein kinase of interest. (asabove)

In another aspect, the present invention comprises a machine readablestorage medium comprising a program containing a set of instructions forcausing a cell screening system to execute the methods disclosed foranalyzing transcription factor or protein kinase activation, wherein thecell screening system comprises an optical system with a stage adaptedfor holding a plate containing cells, a digital camera, a means fordirecting fluorescence or luminescence emitted from the cells to thedigital camera, and a computer means for receiving and processing thedigital data from the digital camera

EXAMPLE 2 Automated Screen for Compounds that Modify Cellular Morphology

Changes in cell size are associated with a number of cellularconditions, such as hypertrophy, cell attachment and spreading,differentiation, growth and division, necrotic and programmed celldeath, cell motility, morphogenesis, tube formation, and colonyformation.

For example, cellular hypertrophy has been associated with a cascade ofalterations in gene expression and can be characterized in cell cultureby an alteration in cell size, that is clearly visible in adherent cellsgrowing on a coverslip.

Cell size can also be measured to determine the attachment and spreadingof adherent cells. Cell spreading is the result of selective binding ofcell surface receptors to substrate ligands and subsequent activation ofsignaling pathways to the cytoskeleton. Cell attachment and spreading tosubstrate molecules is an important step for the metastasis of cancercells, leukocyte activation during the inflammatory response,keratinocyte movement during wound healing, and endothelial cellmovement during angiogenesis. Compounds that affect these surfacereceptors, signaling pathways, or the cytoskeleton will affect cellspreading and can be screened by measuring cell size.

Total cellular area can be monitored by labeling the entire cell body orthe cell cytoplasm using cytoskeletal markers, cytosolic volume markers,or cell surface markers, in conjunction with a DNA label. Examples ofsuch labels (many available from Molecular Probes (Eugene, Oreg.) andSigma Chemical Co. (St. Louis, Mo.)) include the following: CELL SIZEAND AREA MARKERS Cytoskeletal Markers ALEXA ™ 488 phalloidin (MolecularProbes. Oregon) Tubulin-green fluorescent protein chimerasCytokeratin-green fluorescent protein chimeras Antibodies tocytoskeletal proteins Cytosolic Volume Markers Green fluorescentproteins Chloromethylfluorescein diacetate (CMFDA) Calcein greenBCECF/AM ester Rhodamine dextran Cell Surface Markers for Lipid,Protein, or Oligosaccharide Dihexadecyl tetramethylindocarbocyanineperchlorate (DiIC16) lipid dyes Triethylammonium propyl dibutylaminostyryl pyridinium (FM 4-64, FM 1-43) lipid dyes MITOTRACKER ™ Green FMLectins to oligosaccarides such as fluorescein concanavalin A or wheatgerm agglutinin SYPRO ™ Red non-specific protein markers Antibodies tovarious surface proteins such as epidermal growth factor Biotin labelingof surface proteins followed by fluorescent strepavidin labeleing

Protocols for cell staining with these various agents are well known tothose skilled in the art. Cells are stained live or after fixation andthe cell area can be measured. For example, live cells stained withDiIC16 have homogeneously labeled plasma membranes, and the projectedcross-sectional area of the cell is uniformly discriminated frombackground by fluorescence intensity of the dye. Live cells stained withcytosolic stains such as CMFDA produce a fluorescence intensity that isproportional to cell thickness. Although cell labeling is dimmer in thinregions of the cell, total cell area can be discriminated frombackground. Fixed cells can be stained with cytoskeletal markers such asALEXA™ 488 phalloidin that label polymerized actin. Phalloidin does nothomogeneously stain the cytoplasm, but still permits discrimination ofthe total cell area from background.

Cellular Hypertrophy

A screen to analyze cellular hypertrophy is implemented using thefollowing strategy. Primary rat myocytes can be cultured in 96 wellplates, treated with various compounds and then fixed and labeled with afluorescent marker for the cell membrane or cytoplasm, or cytoskeleton,such as an antibody to a cell surface marker or a fluorescent marker forthe cytoskeleton like rhodamine-phalloidin, in combination with a DNAlabel like Hoechst.

After focusing on the Hoechst labeled nuclei, two images are acquired,one of the Hoechst labeled nuclei and one of the fluorescent cytoplasmimage. The nuclei are identified by thresholding to create a mask andthen comparing the morphological descriptors of the mask with a set ofuser defined descriptor values. Each non-nucleus image (or “cytoplasmicimage”) is then processed separately. The original cytoplasm image canbe thresholded, creating a cytoplasmic mask image. Local regionscontaining cells are defined around the nuclei. The limits of the cellsin those regions are then defined by a local dynamic threshold operationon the same region in the fluorescent antibody image. A sequence oferosions and dilations is used to separate slightly touching cells and asecond set of morphological descriptors is used to identify singlecells. The area of the individual cells is tabulated in order to definethe distribution of cell sizes for comparison with size data from normaland hypertrophic cells.

Responses from entire 96-well plates (measured as average cytoplasmicarea/cell) were analyzed by the above methods, and the resultsdemonstrated that the assay will perform the same on a well-to-well,plate-to-plate, and day-to-day basis (below a 15% cov for maximumsignal). The data showed very good correlation for each day, and thatthere was no variability due to well position in the plate.

The following totals can be computed for the field. The aggregate wholenucleus area is the number of nonzero pixels in the nuclear mask. Theaverage whole nucleus area is the aggregate whole nucleus area dividedby the total number of nuclei. For each cytoplasm image several valuescan be computed. These are the total cytoplasmic area, which is thecount of nonzero pixels in the cytoplasmic mask. The aggregate cytoplasmintensity is the sum of the intensities of all pixels in the cytoplasmicmask. The cytoplasmic area per nucleus is the total cytoplasmic areadivided by the total nucleus count. The cytoplasmic intensity pernucleus is the aggregate cytoplasm intensity divided by the totalnucleus count. The average cytoplasm intensity is the aggregatecytoplasm intensity divided by the cytoplasm area. The cytoplasm nucleusratio is the total cytoplasm area divided by the total nucleus area.

Additionally, one or more fluorescent antibodies to other cellularproteins, such as the major muscle proteins actin or myosin, can beincluded. Images of these additional labeled proteins can be acquiredand stored with the above images, for later review, to identifyanomalies in the distribution and morphology of these proteins inhypertrophic cells. This example of a multi-parametric screen allows forsimultaneous analysis of cellular hypertrophy and changes in actin ormyosin distribution.

One of skill in the art will recognize that while the example analyzesmyocyte hypertrophy, the methods can be applied to analyzinghypertrophy, or general morphological changes in any cell type.

Cell Morphology Assays for Prostate Carcinoma

Cell spreading is a measure of the response of cell surface receptors tosubstrate attachment ligands. Spreading is proportional to the ligandconcentration or to the concentration of compounds that reducereceptor-ligand function. One example of selective cell-substrateattachment is prostate carcinoma cell adhesion to the extracellularmatrix protein collagen. Prostate carcinoma cells metastasize to bonevia selective adhesion to collagen.

Compounds that interfere with metastasis of prostate carcinoma cellswere screened as follows. PC3 human prostate carcinoma cells werecultured in media with appropriate stimulants and are passaged tocollagen coated 96 well plates. Ligand concentration can be varied orinhibitors of cell spreading can be added to the wells. Examples ofcompounds that can affect spreading are receptor antagonists such asintegrin- or proteoglycan-blocking antibodies, signaling inhibitorsincluding phosphatidyl inositol-3 kinase inhibitors, and cytoskeletalinhibitors such as cytochalasin D. After two hours, cells were fixed andstained with ALEXA™ 488 phalloidin (Molecular Probes) and Hoechst 33342as per the protocol for cellular hypertrophy. The size of cells underthese various conditions, as measured by cytoplasmic staining, can bedistinguished above background levels. The number of cells per field isdetermined by measuring the number of nuclei stained with the HoechstDNA dye. The area per cell is found by dividing the cytoplasmic area(phalloidin image) by the cell number (Hoechst image). The size of cellsis proportional to the ligand-receptor function. Since the area isdetermined by ligand concentration and by the resultant function of thecell, drug efficacy, as well as drug potency, can be determined by thiscell-based assay. Other measurements can be made as discussed above forcellular hypertrophy.

The methods for analyzing cellular morphology can be used in a combinedhigh throughput-high content screen. In one example, the high throughputmode scans the whole well for an increase in fluorescent phalloidinintensity. A threshold is set above which both nuclei (Hoechst) andcells (phalloidin) are measured in a high content mode. In anotherexample, an environmental biosensor (examples include, but are notlimited to, those biosensors that are sensitive to calcium and pHchanges) is added to the cells, and the cells are contacted with acompound. The cells are scanned in a high throughput mode, and thosewells that exceed a pre-determined threshold for luminescence of thebiosensor are scanned in a high content mode.

In a further aspect, kits are provided for analyzing cellularmorphology, comprising a luminescent compound that can be used tospecifically label the cell cytoplasm, membrane, or cytoskeleton (suchas those described above), and instructions for using the luminescentcompound to identify test stimuli that induce or inhibit changes incellular morphology according to the above methods. In a preferredembodiment, the kit further comprises a luminescent marker for cellnuclei. In a further preferred embodiment, the kit comprises at leastone compound that is known to modify cellular morphology, including, butnot limited to integrin- or proteoglycan-blocking antibodies, signalinginhibitors including phosphatidyl inositol-3 kinase inhibitors, andcytoskeletal inhibitors such as cytochalasin D.

In another aspect, the present invention comprises a machine readablestorage medium comprising a program containing a set of instructions forcausing a cell screening system to execute the disclosed methods foranalyzing cellular morphology, wherein the cell screening systemcomprises an optical system with a stage adapted for holding a platecontaining cells, a digital camera, a means for directing fluorescenceor luminescence emitted from the cells to the digital camera, and acomputer means for receiving and processing the digital data from thedigital camera

EXAMPLE 3 Dual Mode High Throughput and High-Content Screen

The following example is a screen for activation of a G-protein coupledreceptor (GPCR) as detected by the translocation of the GPCR from theplasma membrane to a proximal nuclear location. This example illustrateshow a high throughput screen can be coupled with a high-content screenin the dual mode System for Cell Based Screening.

G-protein coupled receptors are a large class of 7 trans-membrane domaincell surface receptors. Ligands for these receptors stimulate a cascadeof secondary signals in the cell, which may include, but are not limitedto, Ca⁺⁺ transients, cyclic AMP production, inositol triphosphate (IP₃)production and phosphorylation. Each of these signals are rapid,occuring in a matter of seconds to minutes, but are also generic. Forexample, many different GPCRs produce a secondary Ca⁺⁺ signal whenactivated. Stimulation of a GPCR also results in the transport of thatGPCR from the cell surface membrane to an internal, proximal nuclearcompartment. This internalization is a much more receptor-specificindicator of activation of a particular receptor than are the secondarysignals described above.

FIG. 19 illustrates a dual mode screen for activation of a GPCR. Cellscarrying a stable chimera of the GPCR with a blue fluorescent protein(BFP) would be loaded with the acetoxymethylester form of Fluo-3, a cellpermeable calcium indicator (green fluorescence) that is trapped inliving cells by the hydrolysis of the esters. They would then bedeposited into the wells of a microtiter plate 601. The wells would thenbe treated with an array of test compounds using a fluid deliverysystem, and a short sequence of Fluo-3 images of the whole microtiterplate would be acquired and analyzed for wells exhibiting a calciumresponse (i.e., high throughput mode). The images would appear like theillustration of the microtiter plate 601 in FIG. 19. A small number ofwells, such as wells C4 and E9 in the illustration, would fluoresce morebrightly due to the Ca⁺⁺ released upon stimulation of the receptors. Thelocations of wells containing compounds that induced a response 602,would then be transferred to the HCS program and the optics switched fordetailed cell by cell analysis of the blue fluorescence for evidence ofGPCR translocation to the perinuclear region. The bottom of FIG. 19illustrates the two possible outcomes of the analysis of the highresolution cell data. The camera images a sub-region 604 of the wellarea 603, producing images of the fluorescent cells 605. In well C4, theuniform distribution of the fluorescence in the cells indicates that thereceptor has not internalized, implying that the Ca⁺⁺ response seen wasthe result of the stimulation of some other signalling system in thecell. The cells in well E9 606 on the other hand, clearly indicate aconcentration of the receptor in the perinuclear region clearlyindicating the full activation of the receptor. Because only a few hitwells have to be analyzed with high resolution, the overall throughputof the dual mode system can be quite high, comparable to the highthroughput system alone.

EXAMPLE 4 Kinetic High Content Screen

The following is an example of a screen to measure the kinetics ofinternalization of a receptor. As described above, the stimulation of aGPCR, results in the internalization of the receptor, with a time courseof about 15 min. Simply detecting the endpoint as internalized or not,may not be sufficient for defining the potency of a compound as a GPCRagonist or antagonist. However, 3 time points at 5 min intervals wouldprovide information not only about potency during the time course ofmeasurement, but would also allow extrapolation of the data to muchlonger time periods. To perform this assay, the sub-region would bedefined as two rows, the sampling interval as 5 minutes and the totalnumber of time points 3. The system would then start by scanning tworows, and then adding reagent to the two rows, establishing the time=0reference. After reagent addition, the system would again scan the tworow sub-region acquiring the first time point data. Since this processwould take about 250 seconds, including scanning back to the beginningof the sub-region, the system would wait 50 seconds to begin acquisitionof the second time point. Two more cycles would produce the three timepoints and the system would move on to the second 2 row sub-region. Thefinal two 2-row sub-regions would be scanned to finish all the wells onthe plate, resulting in four time points for each well over the wholeplate. Although the time points for the wells would be offset slightlyrelative to time=0, the spacing of the time points would be very closeto the required 5 minutes, and the actual acquisition times and resultsrecorded with much greater precision than in a fixed-cell screen.

EXAMPLE 5 High-Content Screen of Human Glucocorticoid ReceptorTranslocation

One class of HCS involves the drug-induced dynamic redistribution ofintracellular constituents. The human glucocorticoid receptor (hGR), asingle “sensor” in the complex environmental response machinery of thecell, binds steroid molecules that have diffused into the cell. Theligand-receptor complex translocates to the nucleus wheretranscriptional activation occurs (Htun et al., Proc. Natl. Acad. Sci.93:4845, 1996).

In general, hormone receptors are excellent drug targets because theiractivity lies at the apex of key intracellular signaling pathways.Therefore, a high-content screen of hGR translocation has distinctadvantage over in vitro ligand-receptor binding assays. The availabilityof up to two more channels of fluorescence in the cell screening systemof the present invention permits the screen to contain two additionalparameters in parallel, such as other receptors, other distinct targetsor other cellular processes.

Plasmid construct. A eukaryotic expression plasmid containing a codingsequence for a green fluorescent protein—human glucocorticoid receptor(GFP-hGR) chimera was prepared using GFP mutants (Palm et al., Nat.Struct. Biol. 4:361 (1997). The construct was used to transfect a humancervical carcinoma cell line (HeLa).

Cell preparation and transfection. HeLa cells (ATCC CCL-2) weretrypsinized and plated using DMEM containing 5% charcoal/dextran-treatedfetal bovine serum (FBS) (HyClone) and 1% penicillin-streptomycin(C-DMEM) 12-24 hours prior to transfection and incubated at 37° C. and5% CO₂. Transfections were performed by calcium phosphateco-precipitation (Graham and Van der Eb, Virology 52:456, 1973; Sambrooket al., (1989). Molecular Cloning: A Laboratory Manual, Second ed. ColdSpring Harbor Laboratory Press, Cold Spring Harbor, 1989) or withLipofectamine (Life Technologies, Gaithersburg, Md.). For the calciumphosphate transfections, the medium was replaced, prior to transfection,with DMEM containing 5% charcoal/dextran-treated FBS. Cells wereincubated with the calcium phosphate-DNA precipitate for 4-5 hours at37° C. and 5% CO₂, washed 3-4 times with DMEM to remove the precipitate,followed by the addition of C-DMEM.

Lipofectamine transfections were performed in serum-free DMEM withoutantibiotics according to the manufacturer's instructions (LifeTechnologies, Gaithersburg, Md.). Following a 2-3 hour incubation withthe DNA-liposome complexes, the medium was removed and replaced withC-DMEM. All transfected cells in 96-well microtiter plates wereincubated at 33° C. and 5% CO₂ for 24-48 hours prior to drug treatment.Experiments were performed with the receptor expressed transiently inHeLa cells.

Dexamethasone induction of GFP-hGR translocation. To obtainreceptor-ligand translocation kinetic data, nuclei of transfected cellswere first labeled with 5 μg/ml Hoechst 33342 (Molecular Probes) inC-DMEM for 20 minutes at 33° C. and 5% CO₂. Cells were washed once inHank's Balanced Salt Solution (HBSS) followed by the addition of 100 nMdexamethasone in HBSS with 1% charcoal/dextran-treated FBS. To obtainfixed time point dexamethasone titration data, transfected HeLa cellswere first washed with DMEM and then incubated at 33° C. and 5% CO₂ for1 h in the presence of 0-1000 nM dexamethasone in DMEM containing 1%charcoal/dextran-treated FBS. Cells were analyzed live or they wererinsed with HBSS, fixed for 15 min with 3.7% formaldehyde in HBSS,stained with Hoechst 33342, and washed before analysis. Theintracellular GFP-hGR fluorescence signal was not diminished by thisfixation procedure.

Image acquisition and analysis. Kinetic data were collected by acquiringfluorescence image pairs (GFP-hGR and Hoechst 33342-labeled nuclei) fromfields of living cells at 1 min intervals for 30 min after the additionof dexamethasone. Likewise, image pairs were obtained from each well ofthe fixed time point screening plates 1 h after the addition ofdexamethasone. In both cases, the image pairs obtained at each timepoint were used to define nuclear and cytoplasmic regions in each cell.Translocation of GFP-hGR was calculated by dividing the integratedfluorescence intensity of GFP-hGR in the nucleus by the integratedfluorescence intensity of the chimera in the cytoplasm or as anuclear-cytoplasmic difference of GFP fluorescence. In the fixed timepoint screen this translocation ratio was calculated from data obtainedfrom at least 200 cells at each concentration of dexamethasone tested.Drug-induced translocation of GFP-hGR from the cytoplasm to the nucleuswas therefore correlated with an increase in the translocation ratio.

Results. FIG. 20 schematically displays the drug-induced cytoplasm 253to nucleus 252 translocation of the human glucocorticoid receptor. Theupper pair of schematic diagrams depicts the localization of GFP-hGRwithin the cell before 250 (A) and after 251 (B) stimulation withdexamethasone. Under these experimental conditions, the drug induces alarge portion of the cytoplasmic GFP-hGR to translocate into thenucleus. This redistribution is quantified by determining the integratedintensities ratio of the cytoplasmic and nuclear fluorescence in treated255 and untreated 254 cells. The lower pair of fluorescence micrographsshow the dynamic redistribution of GFP-hGR in a single cell, before 254and after 255 treatment. The HCS is performed on wells containinghundreds to thousands of transfected cells and the translocation isquantified for each cell in the field exhibiting GFP fluorescence.Although the use of a stably transfected cell line would yield the mostconsistently labeled cells, the heterogeneous levels of GFP-hGRexpression induced by transient transfection did not interfere withanalysis by the cell screening system of the present invention.

To execute the screen, the cell screening system scans each well of theplate, images a population of cells in each, and analyzes cellsindividually. Here, two channels of fluorescence are used to define thecytoplasmic and nuclear distribution of the GFP-hGR within each cell.Depicted in FIG. 21 is the graphical user interface of the cellscreening system near the end of a GFP-hGR screen. The user interfacedepicts the parallel data collection and analysis capability of thesystem. The windows labeled “Nucleus” 261 and “GFP-hGR” 262 show thepair of fluorescence images being obtained and analyzed in a singlefield. The window labeled “Color Overlay” 260 is formed bypseudocoloring the above images and merging them so the user canimmediately identify cellular changes. Within the “Stored ObjectRegions” window 265, an image containing each analyzed cell and itsneighbors is presented as it is archived. Furthermore, as the HCS dataare being collected, they are analyzed, in this case for GFP-hGRtranslocation, and translated into an immediate “hit” response. The 96well plate depicted in the lower window of the screen 267 shows whichwells have met a set of user-defined screening criteria For example, awhite-colored well 269 indicates that the drug-induced translocation hasexceeded a predetermined threshold value of 50%. On the other hand, ablack-colored well 270 indicates that the drug being tested induced lessthan 10% translocation. Gray-colored wells 268 indicate “hits” where thetranslocation value fell between 10% and 50%. Row “E” on the 96 wellplate being analyzed 266 shows a titration with a drug known to activateGFP-hGR translocation, dexamethasone. This example screen used only twofluorescence channels. Two additional channels (Channels 3 263 and 4264) are available for parallel analysis of other specific targets, cellprocesses, or cytotoxicity to create multiple parameter screens.

There is a link between the image database and the information databasethat is a powerful tool during the validation process of new screens. Atthe completion of a screen, the user has total access to image andcalculated data (FIG. 22). The comprehensive data analysis package ofthe cell screening system allows the user to examine HCS data atmultiple levels. Images 276 and detailed data in a spread sheet 279 forindividual cells can be viewed separately, or summary data can beplotted. For example, the calculated results of a single parameter foreach cell in a 96 well plate are shown in the panel labeled Graph 1 275.By selecting a single point in the graph, the user can display theentire data set for a particular cell that is recalled from an existingdatabase. Shown here are the image pair 276 and detailed fluorescenceand morphometric data from a single cell (Cell #118, gray line 277). Thelarge graphical insert 278 shows the results of dexamethasoneconcentration on the translocation of GFP-hGR. Each point is the averageof data from at least 200 cells. The calculated EC₅₀ for dexamethasonein this assay is 2 nM.

A powerful aspect of HCS with the cell screening system is thecapability of kinetic measurements using multicolor fluorescence andmorphometric parameters in living cells. Temporal and spatialmeasurements can be made on single cells within a population of cells ina field. FIG. 23 shows kinetic data for the dexamethasone-inducedtranslocation of GFP-hGR in several cells within a single field. HumanHeLa cells transfected with GFP-hGR were treated with 100 nMdexamethasone and the translocation of GFP-hGR was measured over time ina population of single cells. The graph shows the response oftransfected cells 285, 286, 287, and 288 and non-transfected cells 289.These data also illustrate the ability to analyze cells with differentexpression levels.

EXAMPLE 6 High-Content Screen of Drug-Induced Apoptosis

Apoptosis is a complex cellular program that involves myriad molecularevents and pathways. To understand the mechanisms of drug action on thisprocess, it is essential to measure as many of these events within cellsas possible with temporal and spatial resolution. Therefore, anapoptosis screen that requires little cell sample preparation yetprovides an automated readout of several apoptosis-related parameterswould be ideal. A cell-based assay designed for the cell screeningsystem has been used to simultaneously quantify several of themorphological, organellar, and macromolecular hallmarks ofpaclitaxel-induced apoptosis.

Cell preparation. The cells chosen for this study were mouse connectivetissue fibroblasts (L-929; ATCC CCL-1) and a highly invasiveglioblastoma cell line (SNB-19; ATCC CRL-2219) (Welch et al., In VitroCell Dev. Biol. 31:610, 1995). The day before treatment with anapoptosis inducing drug, 3500 cells were placed into each well of a96-well plate and incubated overnight at 37° C. in a humidified 5% CO₂atmosphere. The following day, the culture medium was removed from eachwell and replaced with fresh medium containing various concentrations ofpaclitaxel (0-50 μM) from a 20 mM stock made in DMSO. The maximalconcentration of DMSO used in these experiments was 0.25%. The cellswere then incubated for 26 h as above. At the end of the paclitaxeltreatment period, each well received fresh medium containing 750 nMMitoTracker Red (Molecular Probes; Eugene, Oreg.) and 3 μg/ml Hoechst33342 DNA-binding dye (Molecular Probes) and was incubated as above for20 min. Each well on the plate was then washed with HBSS and fixed with3.7% formaldehyde in HBSS for 15 min at room temperature. Theformaldehyde was washed out with HBSS and the cells were permeabilizedfor 90 s with 0.5% (v/v) Triton X-100, washed with HBSS, incubated with2 U ml⁻¹ Bodipy FL phallacidin (Molecular Probes) for 30 min, and washedwith HBSS. The wells on the plate were then filled with 200 μl HBSS,sealed, and the plate stored at 4° C. if necessary. The fluorescencesignals from plates stored this way were stable for at least two weeksafter preparation. As in the nuclear translocation assay, fluorescencereagents can be designed to convert this assay into a live cellhigh-content screen.

Image acquisition and analysis on the ArrayScan System. The fluorescenceintensity of intracellular MitoTracker Red, Hoechst 33342, and Bodipy FLphallacidin was measured with the cell screening system as describedsupra. Morphometric data from each pair of images obtained from eachwell was also obtained to detect each object in the image field (e.g.,cells and nuclei), and to calculate its size, shape, and integratedintensity.

Calculations and output A total of 50-250 cells were measured per imagefield. For each field of cells, the following calculations wereperformed: (1) The average nuclear area (μm²) was calculated by dividingthe total nuclear area in a field by the number of nuclei detected. (2)The average nuclear perimeter (μm) was calculated by dividing the sum ofthe perimeters of all nuclei in a field by the number of nuclei detectedin that field. Highly convoluted apoptotic nuclei had the largestnuclear perimeter values. (3) The average nuclear brightness wascalculated by dividing the integrated intensity of the entire field ofnuclei by the number of nuclei in that field. An increase in nuclearbrightness was correlated with increased DNA content. (4) The averagecellular brightness was calculated by dividing the integrated intensityof an entire field of cells stained with MitoTracker dye by the numberof nuclei in that field. Because the amount of MitoTracker dye thataccumulates within the mitochondria is proportional to the mitochondrialpotential, an increase in the average cell brightness is consistent withan increase in mitochondrial potential. (5) The average cellularbrightness was also calculated by dividing the integrated intensity ofan entire field of cells stained with Bodipy FL phallacidin dye by thenumber of nuclei in that field. Because the phallotoxins bind with highaffinity to the polymerized form of actin, the amount of Bodipy FLphallacidin dye that accumulates within the cell is proportional toactin polymerization state. An increase in the average cell brightnessis consistent with an increase in actin polymerization.

Results. FIG. 24 (top panels) shows the changes paclitaxel induced inthe nuclear morphology of L-929 cells. Increasing amounts of paclitaxelcaused nuclei to enlarge and fragment 293, a hallmark of apoptosis.Quantitative analysis of these and other images obtained by the cellscreening system is presented in the same figure. Each parametermeasured showed that the L-929 cells 296 were less sensitive to lowconcentrations of paclitaxel than were SNB-19 cells 297. At higherconcentrations though, the L-929 cells showed a response for eachparameter measured. The multiparameter approach of this assay is usefulin dissecting the mechanisms of drug action. For example, the area,brightness, and fragmentation of the nucleus 298 and actinpolymerization values 294 reached a maximum value when SNB-19 cells weretreated with 10 nM paclitaxel (FIG. 24; top and bottom graphs). However,mitochondrial potential 295 was minimal at the same concentration ofpaclitaxel (FIG. 24; middle graph). The fact that all the parametersmeasured approached control levels at increasing paclitaxelconcentrations (>10 nM) suggests that SNB-19 cells have low affinitydrug metabolic or clearance pathways that are compensatory atsufficiently high levels of the drug. Contrasting the drug sensitivityof SNB-19 cells 297, L-929 showed a different response to paclitaxel296. These fibroblastic cells showed a maximal response in manyparameters at 5 μM paclitaxel, a 500-fold higher dose than SNB-19 cells.Furthermore, the L-929 cells did not show a sharp decrease inmitochondrial potential 295 at any of the paclitaxel concentrationstested. This result is consistent with the presence of unique apoptosispathways between a normal and cancer cell line. Therefore, these resultsindicate that a relatively simple fluorescence labeling protocol can becoupled with the cell screening system of the present invention toproduce a high-content screen of key events involved in programmed celldeath.

EXAMPLE 7 Protease Induced Translocation of a Signaling EnzymeContaining a Disease-Associated Sequence from Cytoplasm to Nucleus

Plasmid construct. A eukaryotic expression plasmid containing a codingsequence for a green fluorescent protein—caspase (Cohen (1997),Biochemical J. 326:1-16; Liang et al. (1997), J. of Molec. Biol.274:291-302) chimera is prepared using GFP mutants. The construct isused to transfect eukaryotic cells.

Cell preparation and transfection. Cells are trypsinized and plated 24 hprior to transfection and incubated at 37° C. and 5% CO₂. Transfectionsare performed by methods including, but not limited to calcium phosphatecoprecipitation or lipofection. Cells are incubated with the calciumphosphate-DNA precipitate for 4-5 hours at 37° C. and 5% CO₂, washed 3-4times with DMEM to remove the precipitate, followed by the addition ofC-DMEM. Lipofectamine transfections are performed in serum-free DMEMwithout antibiotics according to the manufacturer's instructions.Following a 2-3 hour incubation with the DNA-liposome complexes, themedium is removed and replaced with C-DMEM

Apopototic induction of Caspase-GFP translocation. To obtain Caspase-GFPtranslocation kinetic data, nuclei of transfected cells are firstlabeled with 5 μg/ml Hoechst 33342 (Molecular Probes) in C-DMEM for 20minutes at 37° C. and 5% CO₂. Cells are washed once in Hank's BalancedSalt Solution (HBSS) followed by the addition of compounds that induceapoptosis. These compounds include, but are not limited to paclitaxel,staurosporine, ceramide, and tumor necrosis factor. To obtain fixed timepoint titration data, transfected cells are first washed with DMEM andthen incubated at 37° C. and 5% CO₂ for 1 h in the presence of 0-1000 nMcompound in DMEM. Cells are analyzed live or they are rinsed with HBSS,fixed for 15 min with 3.7% formaldehyde in HBSS, stained with Hoechst33342, and washed before analysis.

Image acquisition and analysis. Kinetic data are collected by acquiringfluorescence image pairs (Caspase-GFP and Hoechst 33342-labeled nuclei)from fields of living cells at 1 min intervals for 30 min after theaddition of compound. Likewise, image pairs are obtained from each wellof the fixed time point screening plates 1 h after the addition ofcompound. In both cases, the image pairs obtained at each time point areused to define nuclear and cytoplasmic regions in each cell.Translocation of Caspase-GFP is calculated by dividing the integratedfluorescence intensity of Caspase-GFP in the nucleus by the integratedfluorescence intensity of the chimera in the cytoplasm or as anuclear-cytoplasmic difference of GFP fluorescence. In the fixed timepoint screen this translocation ratio is calculated from data obtainedfrom at least 200 cells at each concentration of compound tested.Drug-induced translocation of Caspase-GFP from the cytoplasm to thenucleus is therefore correlated with an increase in the translocationratio. Molecular interaction libraries including, but not limited tothose comprising putative activators or inhibitors ofapoptosis-activated enzymes are use to screen the indicator cell linesand identify a specific ligand for the DAS, and a pathway activated bycompound activity.

EXAMPLE 8 Identification of Novel Steroid Receptors from DAS

Two sources of material and/or information are required to make use ofthis embodiment, which allows assessment of the function of anuncharacterized gene. First, disease associated sequence bank(s)containing cDNA sequences suitable for transfection into mammalian cellscan be used. Because every RADE or differential expression experimentgenerates up to several hundred sequences, it is possible to generate anample supply of DAS. Second, information from primary sequence databasesearches can be used to place DAS into broad categories, including, butnot limited to, those that contain signal sequences, seventrans-membrane motifs, conserved protease active site domains, or otheridentifiable motifs. Based on the information acquired from thesesources, method types and indicator cell lines to be transfected areselected. A large number of motifs are already well characterized andencoded in the linear sequences contained within the large number genesin existing genomic databases.

In one embodiment, the following steps are taken:

-   -   1) Information from the DAS identification experiment (including        database searches) is used as the basis for selecting the        relevant biological processes. (for example, look at the DAS        from a tumor line for cell cycle modulation, apoptosis,        metastatic proteases, etc.)    -   2) Sorting of DNA sequences or DAS by identifiable motifs (ie.        signal sequences, 7-transmembrane domains, conserved protease        active site domains, etc.) This initial grouping will determine        fluorescent tagging strategies, host cell lines, indicator cell        lines, and banks of bioactive molecules to be screened, as        described supra.    -   3) Using well established molecular biology methods, ligate DAS        into an expression vector designed for this purpose. Generalized        expression vectors contain promoters, enhancers, and terminators        for which to deliver target sequences to the cell for transient        expression. Such vectors may also contain antibody tagging        sequences, direct association sequences, chromophore fusion        sequences like GFP, etc. to facilitate detection when expressed        by the host.    -   4) Transiently transfect cells with DAS containing vectors using        standard transfection protocols including: calcium phosphate        co-precipitation, liposome mediated, DEAE dextran mediated,        polycationic mediated, viral mediated, or electroporation, and        plate into microtiter plates or microwell arrays. Alternatively,        transfection can be done directly in the microtiter plate        itself.    -   5) Carry out the cell screening methods as described supra.

In this embodiment, DAS shown to possess a motif(s) suggestive oftranscriptional activation potential (for example, DNA binding domain,amino terminal modulating domain, hinge region, or carboxy terminalligand binding domain) are utilized to identify novel steroid receptors.

Defining the fluorescent tags for this experiment involvesidentification of the nucleus through staining, and tagging the DAS bycreating a GFP chimera via insertion of DAS into an expression vector,proximally fused to the gene encoding GFP. Alternatively, a single chainantibody fragment with high affinity to some portion of the expressedDAS could be constructed using technology available in the art(Cambridge Antibody Technologies) and linked to a fluorophore (FITC) totag the putative transcriptional activator/receptor in the cells. Thisalternative would provide an external tag requiring no DNA transfectionand therefore would be useful if distribution data were to be gatheredfrom the original primary cultures used to generate the DAS.

Plasmid construct. A eukaryotic expression plasmid containing a codingsequence for a green fluorescent protein—DAS chimera is prepared usingGFP mutants. The construct is used to transfect HeLa cells. The plasmid,when transfected into the host cell, produces a GFP fused to the DASprotein product, designated GFP-DASpp.

Cell preparation and transfection. HeLa cells are trypsinized and platedusing DMEM containing 5% charcoal/dextran-treated fetal bovine serum(FBS) (Hyclone) and 1% penicillin-streptomycin (C-DMEM) 12-24 hoursprior to transfection and incubated at 37° C. and 5% CO₂. Transfectionsare performed by calcium phosphate coprecipitation or with Lipofectamine(Life Technologies). For the calcium phosphate transfections, the mediumis replaced, prior to transfection, with DMEM containing 5%charcoal/dextran-treated FBS. Cells are incubated with the calciumphosphate-DNA precipitate for 4-5 hours at 37° C. and 5% CO₂, and washed3-4 times with DMEM to remove the precipitate, followed by the additionof C-DMEM. Lipofectamine transfections are performed in serum-free DMEMwithout antibiotics according to the manufacturer's instructions.Following a 2-3 hour incubation with the DNA-liposome complexes, themedium is removed and replaced with C-DMEM. All transfected cells in96-well microtiter plates are incubated at 33° C. and 5% CO₂ for 24-48hours prior to drug treatment. Experiments are performed with thereceptor expressed transiently in HeLa cells.

Localization of expressed GFP-DASpp inside cells. To obtain cellulardistribution data, nuclei of transfected cells are first labeled with 5μg/ml Hoechst 33342 (Molecular Probes) in C-DMEM for 20 minutes at 33°C. and 5% CO₂. Cells are washed once in Hank's Balanced Salt Solution(HBSS). The cells are analyzed live or they are rinsed with HBSS, fixedfor 15 min with 3.7% formaldehyde in HBSS, stained with Hoechst 33342,and washed before analysis.

In a preferred embodiment, image acquisition and analysis are performedusing the cell screening system of the present invention. Theintracellular GFP-DASpp fluorescence signal is collected by acquiringfluorescence image pairs (GFP-DASpp- and Hoechst 33342-labeled nuclei)from field cells. The image pairs obtained at each time point are usedto define nuclear and cytoplasmic regions in each cell. Datademonstrating dispersed signal in the cytoplasm would be consistent withknown steroid receptors that are DNA transcriptional activators.

Screening for induction of GFP-DASpp translocation. Using the aboveconstruct, confirmed for appropriate expression of the GFP-DASpp, as anindicator cell line, a screen of various ligands is performed using aseries of steroid type ligands including, but not limited to: estrogen,progesterone, retinoids, growth factors, androgens, and many othersteroid and steroid based molecules. Image acquisition and analysis areperformed using the cell screening system of the invention. Theintracellular GFP-DASpp fluorescence signal is collected by acquiringfluorescence image pairs (GFP-DASpp and Hoechst 33342-labeled nuclei)from fields cells. The image pairs obtained at each time point are usedto define nuclear and cytoplasmic regions in each cell. Translocation ofGFP-DASpp is calculated by dividing the integrated fluorescenceintensity of GFP-DASpp in the nucleus by the integrated fluorescenceintensity of the chimera in the cytoplasm or as a nuclear-cytoplasmicdifference of GFP fluorescence. A translocation from the cytoplasm intothe nucleus indicates a ligand binding activation of the DASpp thusidentifying the potential receptor class and action. Combining this datawith other data obtained in a similar fashion using known inhibitors andmodifiers of steroid receptors, would either validate the DASpp as atarget, or more data would be generated from various sources.

EXAMPLE 9 Intracellular Microtubule Stability

In another aspect of the invention, an automated method for identifyingcompounds that modify microtubule structure is provided. In thisembodiment, indicator cells are treated with test compounds and thedistribution of luminescent microtubule-labeling molecules is measuredin space and time using a cell screening system, such as the onedisclosed above. The luminescent microtubule-labeling molecules may beexpressed by or added to the cells either before, together with, orafter contacting the cells with a test compound.

In one embodiment of this aspect of the invention, living cells expressa luminescently labeled protein biosensor of microtubule dynamics,comprising a protein that labels microtubules fused to a luminescentprotein. Appropriate microtubule-labeling proteins for this aspect ofthe invention include, but are not limited to α and β tubulin isoforms,and MAP4. Preferred embodiments of the luminescent protein include, butare not limited to green fluorescent protein (GFP) and GFP mutants. In apreferred embodiment, the method involves transfecting cells with amicrotubule labeling luminescent protein, wherein the microtubulelabeling protein can be, but is not limited to, α-tubulin, β-tubulin, ormicrotubule-associated protein 4 (MAP4). The approach outlined hereenables those skilled in the art to make live cell measurements todetermine the effect of lead compounds on tubulin activity andmicrotubule stability in vivo.

In a most preferred embodiment, MAP4 is fused to a modified version ofthe Aequorea Victoria green fluorescent protein (GFP). A DNA constructhas been made which consists of a fusion between the EGFP codingsequence (available from Clontech) and the coding sequence for mouseMAP4. (Olson et al., (1995), J. Cell Biol. 130(3): 639-650). MAP4 is aubiquitous microtubule-associated protein that is known to interact withmicrotubules in interphase as well as mitotic cells (Olmsted andMurofushi, (1993), MAP4. In “Guidebook to the Cytoskeleton and MotorProteins.” Oxford University Press. T. Kreis and R. Vale, eds.) Itslocalization, then, can serve as an indicator of the localization,organization, and integrity of microtubules in living (or fixed) cellsat all stages of the cell cycle for cell-based HCS assays. While MAP2and tau (microtubule associated proteins expressed specifically inneuronal cells) have been used to form GFP chimeras (Kaech et al.,(1996) Neuron. 17: 1189-1199; Hall et al., (1997), Proc. Nat. Acad. Sci.94: 4733-4738) their restricted cell type distribution and the tendencyof these proteins to bundle microtubules when overexpressed make theseproteins less desirable as molecular reagents for analysis in live cellsoriginating from varied tissues and organs. Moderate overexpression ofGFP-MAP4 does not disrupt microtubule function or integrity (Olson etal., 1995). Similar constructs can be made using β-tubulin or α-tubulinvia standard techniques in the art. These chimeras will provide a meansto observe and analyze microtubule activity in living cells during allstages of the cell cycle.

In another embodiment, the luminescently labeled protein biosensor ofmicrotubule dynamics is expressed, isolated, and added to the cells tobe analyzed via bulk loading techniques, such as microinjection, scrapeloading, and impact-mediated loading. In this embodiment, there is notan issue of overexpression within the cell, and thus α and β tubulinisoforms, MAP4, MAP2 and/or tau can all be used.

In a further embodiment, the protein biosensor is expressed by the cell,and the cell is subsequently contacted with a luminescent label, such asa labeled antibody, that detects the protein biosensor, endogenouslevels of a protein antigen, or both. In this embodiment, a luminescentlabel that detects α and β tubulin isoforms, MAP4, MAP2 and/or tau, canbe used.

A variety of GFP mutants are available, all of which would be effectivein this invention, including, but not limited to, GFP mutants which arecommercially available (Clontech, California).

The MAP4 construct has been introduced into several mammalian cell lines(BHK-21, Swiss 3T3, HeLa, HEK 293, LLCPK) and the organization andlocalization of tubulin has been visualized in live cells by virtue ofthe GFP fluorescence as an indicator of MAP4 localization. The constructcan be expressed transiently or stable cell lines can be prepared bystandard methods. Stable HeLa cell lines expressing the EGFP-MAP4chimera have been obtained, indicating that expression of the chimera isnot toxic and does not interfere with mitosis.

Possible selectable markers for establishment and maintenance of stablecell lines include, but are not limited to the neomycin resistance gene,hygromycin resistance gene, zeocin resistance gene, puromycin resistancegene, bleomycin resistance gene, and blastacidin resistance gene.

The utility of this method for the monitoring of microtubule assembly,disassembly, and rearrangement has been demonstrated by treatment oftransiently and stably transfected cells with microtubule drugs such aspaclitaxel, nocodazole, vincristine, or vinblastine.

The present method provides high-content and combined highthroughput-high content cell-based screens for anti-microtubule drugs,particularly as one parameter in a multi-parametric cancer targetscreen. The EGFP-MAP4 construct used herein can also be used as one ofthe components of a high-content screen that measures multiple signalingpathways or physiological events. In a preferred embodiment, a combinedhigh throughput and high content screen is employed, wherein multiplecells in each of the locations containing cells are analyzed in a highthroughput mode, and only a subset of the locations containing cells areanalyzed in a high content mode. The high throughput screen can be anyscreen that would be useful to identify those locations containing cellsthat should be further analyzed, including, but not limited to,identifying locations with increased luminescence intensity, thoseexhibiting expression of a reporter gene, those undergoing calciumchanges, and those undergoing pH changes.

In addition to drug screening applications, the present invention may beapplied to clinical diagnostics, the detection of chemical andbiological warfare weapons, and the basic research market sincefundamental cell processes, such as cell division and motility, arehighly dependent upon microtubule dynamics.

Image Acquisition and Analysis

Image data can be obtained from either fixed or living indicator cells.To extract morphometric data from each of the images obtained thefollowing method of analysis is used:

-   1. Threshold each nucleus and cytoplasmic image to produce a mask    that has value=0 for each pixel outside a nucleus or cell boundary.-   2. Overlay the mask on the original image, detect each object in the    field (i.e., nucleus or cell), and calculate its size, shape, and    integrated intensity.-   3. Overlay the whole cell mask obtained above on the corresponding    luminescent microtubule image and apply one or more of the following    set of classifiers to determine the micrtotubule morphology and the    effect of drugs on microtubule morphology.

Microtubule morphology is defined using a set of classifiers to quantifyaspects of microtubule shape, size, aggregation state, andpolymerization state. These classifiers can be based on approaches thatinclude co-occurrence matrices, texture measurements, spectral methods,structural methods, wavelet transforms, statistical methods, orcombinations thereof. Examples of such classifiers are as follows:

-   -   1. A classifier to quantify microtubule length and width using        edge detection methods such as that discussed in Kolega et al.        ((1993). BioImaging 1:136-150), which discloses a non-automated        method to determine edge strength in individual cells), to        calculate the total edge strength within each cell. To normalize        for cell size, the total edge strength can be divided by the        cell area to give a “microtubule morphology” value. Large        microtubule morphology values are associated with strong edge        strength values and are therefore maximal in cells containing        distinct microtubule structures. Likewise, small microtubule        morphology values are associated with weak edge strength and are        minimal in cells with depolymerized microtubules. The        physiological range of microtubule morphology values is set by        treating cells with either the microtubule stabilizing drug        paclitaxel (10 μM) or the microtubule depolymerizing drug        nocodazole (10 μg/ml).    -   2. A classifier to quantify microtubule aggregation into        punctate spots or foci using methodology from the receptor        internalization methods discussed supra.    -   3. A classifier to quantify microtubule depolymerization using a        measure of image texture.    -   4. A classifier to quantify apparent interconnectivity, or        branching (or both), of the microtubules.    -   5. Measurement of the kinetics of microtubule reorganization        using the above classifiers on a time series of images of cells        treated with test compounds.

In a further aspect, kits are provided for analyzing microtubulestability, comprising an expression vector comprising a nucleic acidthat encodes a microtubule labeling protein and instructions for usingthe expression vector for carrying out the methods described above. In apreferred embodiment, the expression vector further comprises a nucleicacid that encodes a luminescent protein, wherein the microtubule bindingprotein and the luminescent protein thereof are expressed as a fusionprotein. Alternatively, the kit may contain an antibody thatspecifically binds to the microtubule-labeling protein. In a furtherembodiment, the kit includes cells that express the microtubule labelingprotein. In a preferred embodiment, the cells are transfected with theexpression vector. In another preferred embodiment, the kits furthercontain a compound that is known to disrupt microtubule structure,including but not limited to curacin, nocodazole, vincristine, orvinblastine. In another preferred embodiment, the kits further comprisea compound that is known to stabilize microtubule structure, includingbut not limited to taxol (paclitaxel), and discodermolide.

In another aspect, the present invention comprises a machine readablestorage medium comprising a program containing a set of instructions forcausing a cell screening system to execute the disclosed methods foranalyzing microtubule stability, wherein the cell screening systemcomprises an optical system with a stage adapted for holding a platecontaining cells, a digital camera, a means for directing fluorescenceor luminescence emitted from the cells to the digital camera, and acomputer means for receiving and processing the digital data from thedigital camera.

EXAMPLE 10 Neurite Outgrowth

A major interest for drug discovery is the identification of compoundsthat affect the growth of neurites from neurons. Drugs that promotenerve growth will be of use for treating a wide variety of diseases andtrauma that result in neuropathy and nerve injury, including but notlimited to spinal cord injury, neuropathy resulting from diseases suchas diabetes and stroke, Parkinson's disease, and other forms of dementiaincluding Alzheimer's disease.

Thus, in another aspect, the present invention provides automatedmethods, kits, and computer readable media for analyzing neuriteoutgrowth. The methods of this embodiment comprise

-   -   providing an array of locations comprising cells, wherein the        cells possess at least a first luminescently labeled reporter        molecule that reports on cell number, and at least a second        luminescently labeled reporter molecule that reports on neurite        outgrowth, wherein the cells comprise neurons;    -   imaging or scanning multiple cells in each of the locations        containing multiple cells to obtain luminescent signals from the        first and second luminescently-labeled reporter molecule;    -   converting the luminescent signals into digital data; and    -   utilizing the digital data to automatically make measurements,        wherein the measurements are used to automatically calculate        changes in the distribution, environment or activity of the        first and second luminescently labeled reporter molecules on or        within the cells, wherein the calculated changes provide a        measure of neurite outgrowth.

As used herein, the term “neurons” or “neuronal cells” includes any cellpopulation that includes neurons of any type, including, but not limitedto, primary cultures of brain cells that contain neurons, isolated cellcultures comprising primary neuronal cells, neuronal precursor cells,tissue culture cells that are used as models of neurons (such as PC12cells, which are a neoplastic neuronal cell line cloned from ratpheochromocytoma), or mixtures thereof.

As used herein, the term “neurite” refers to any processes and/orstructures that grow from a neuron's cell body including but not limitedto axons, dendrites, neurites, intermediate segments, terminal segments,filopodia and growth cones.

As used herein, the phrase “neurite outgrowth” includes positive neuriteoutgrowth, neurite outgrowth inhibition, neurite outgrowth degradation,and other changes in neurite morphology.

As used herein, the phrase “the cells possess one or more luminescentreporter molecules” means that the luminescent reporter molecule may beexpressed as a luminescent reporter molecule by the cells, added to thecells as a luminescent reporter molecule, or luminescently labeled bycontacting the cell with a luminescently labeled molecule that binds tothe reporter molecule, such as a dye or antibody, that binds to thereporter molecule. The luminescent reporter molecule can be expressed oradded to the cell either before, simultaneously with, or after treatmentwith the test substance.

In another embodiment, the method further comprises contacting theneurons with a test compound, and wherein the calculated changesindicate whether the test compound has modified neurite outgrowth in theneurons. If a mixed cell culture is used, and the nuclei of the othercells in the mixed culture are to be identified, such as the astrocytes,oligodendrocytes, or microglia, then fluorescent probes that arespecific to those cell types and are labeled with a differentfluorophore are used, and sufficient images per field (i.e. more thantwo) are acquired to identify astrocytes, oligodendrocytes, ormicroglia. This embodiment of the invention can be used to discovercompounds that affect (positively or negatively) neurite outgrowth fromneuronal cells, as well to identify conditions that are toxic to neuronsand affect their neurites' morphology, including without limitationneurite length, number, and branching. For such neurotoxicity studies,the method would comprise identifying compounds that degrade neurites,or identifying test compounds that inhibit the activity of knownneurotoxins.

In a preferred embodiment, the first luminescently labeled reportermolecule comprises a DNA binding compound. In a further preferredembodiment, the second luminescently labeled reporter molecule comprisesa compound that selectively detects a cell component selected from thegroup consisting of cytoplasm, membrane, and cellular proteins. In afurther embodiment, the second luminescently labeled reporter moleculeis neuron-specific. In another embodiment, the cells comprise at least athird luminescently labeled reporter molecule that is neuron-specific,or specific to other cell types of interest, including but not limitedto microglia, oligodendrocytes, and astrocytes.

In another embodiment, the method further comprises contacting the cellswith a control compound known to modify neurite outgrowth, and utilizingthe calculated changes to determine whether the test stimulus inhibitedthe control compound from modifying neurite outgrowth in the neurons.Alternatively, no test stimulus is added, and the measurements andcalculated changes are made after removal of the control compound, todetermine the effects of such removal on neurite outgrowth.

In a further embodiment, sub-regions of the array of locations aresampled multiple times at intervals to provide kinetic measurementchanges in the distribution, environment or activity of the luminescentreporter molecules on or within the cells

In addition, other high content or high throughput assays, includingwithout limitation those described throughout the application, can beused in combination with the present assay, to measure the physiologicalstate of the same neurons upon compound treatment. Preferred assays foruse in a multiparametric assay with the present method are cellviability assays, apoptosis assays, and G-protein coupled receptor(GPCR) and other receptor internalization assays.

This aspect of the invention provides a way to automatically scan arraysof cell populations treated with different compounds and automaticallyquantify the neurite outgrowth of the neuronal cells both collectivelyand individually. The neurons do not have to be isolated from a mixtureof different cell types or different neuronal cell types to be used inthis embodiment, and thus the method can be applied to primary braincultures.

The present invention further provides computer readable storage mediacomprising a program containing a set of instructions for causing a cellscreening system to execute the methods of this aspect of the invention,wherein the cell screening system comprises an optical system with astage adapted for holding a plate containing cells, a means for movingthe stage or the optical system, a digital camera, a means for directinglight emitted from the cells to the digital camera, and a computer meansfor receiving and processing the digital data from the digital camera.In a preferred embodiment, the cell screening system is that disclosedabove.

The invention further provides kits for analyzing neurite outgrowth, orfor identifying compounds that modify neurite outgrowth, comprising atleast one neuron-specific luminescent reporter molecule; at least onenucleus-specific luminescent reporter molecule; and instructions forusing the neuron-specific luminescent reporter molecule and thenucleus-specific luminescent reporter molecule to analyze neuriteoutgrowth, or to identify compounds that modify neurite outgrowth.

Identification of Neurons

In one embodiment, all cells in the sample are labeled with aluminescent reporter molecule marker to identify their locations. Oncethe cell locations are identified, a cell count can be made. Typically,the nucleic acid dye Hoechst 33342 is used as a luminescent reportermolecule to identify the nuclei of all the cells. However, other nuclearlabels can also be used. Nucleic acid fluorescent stains are of twokinds: those that can cross the plasma membrane of live cells, and thosethat are membrane impermeant. Examples of membrane permeant nucleic acidstains include DAPI, dihydroethidium, hexidium iodide, Hoechst 33258,and the SYTO® dye series (Molecular Probes). To label nuclei withmembrane-impermeant dyes, the plasma membrane has to be permeabilized.Examples of membrane-impermeant nucleic acid dyes include cyaninenucleic acid labels such as TOTO®, YOYO®, BOBO™, POPO™, TO-PRO®,YO-PRO®, BO-PRO™ and PO-PRO™ (Molecular Probes), ethidium analogs suchas ethidium-acridine heterodimer, ethidium bromide, ethidium diazide andethidium homodimers 1 and 2, propidium iodide, and the green nucleicacid stain SYTOX® (Molecular Probes). In addition, other components ofthe cells, such as the cytoplasm, can be labeled to identify all of thecells in the culture if the neurons are sparsely plated. In a preferredembodiment, a nuclear label is used. Examples of some cytoplasmic stainsare given below.

If the sample consists of a mixture of brain cells (including cell typesother than neurons), the luminescently labeled nuclei that belong toneurons are identified. The neurons are distinguished from the othercells by a neuronal specific luminescent reporter molecule withluminescence of a different wavelength from the nuclei marker and anyother cell markers or other luminescent reporter molecules that arebeing used. The nuclei that coincide with the neuron-specific marker areidentified as those nuclei in the mixed cell population that belong toneurons. There are many different neuron-specific labeling markers thatcan be used. Some examples of neuron specific labeling strategiesinclude, but are not limited to: indirect immunofluorescence againstneurofilaments, indirect immunofluorescence against βIII-tubulin, andindirect immunofluorescence against neurotrophic factors such as theciliary neurotrophic factor (CNTF), all being neuron-specific antigensand proteins.

The cells are luminescently labeled so all of their processes can bevisualized, whether the culture consists only of neurons orneuronal-like cells, or neurons in a mixed cell culture. There areseveral targets on neurons that can be luminescently labeled to allowvisualization of the processes:

-   (1) Cytoplasmic Staining: The cytoplasm can be stained with any    standard cytoplasmic stain. Examples of such stains are CMFDA    (chloromethyl fluorescein diacetate), or CMTMR (chloromethyl    tetramethylrhodamine) (Molecular Probes). Alternatively, the cells    can be engineered to express an autofluorescent protein such as    Green Fluorescent Protein (GFP). The expressed GFP in the cytoplasm    will allow the neuron's processes to be visualized.-   (2) Membrane Staining: The membrane stain can either be a standard    lipid dye such as diI (dioctadecylindocarbocyanine) (Molecular    Probes), or can be a fluorescently labeled protein that is on the    cell's membrane. To fluorescently label proteins, one can use either    immunofluorescence against cell surface proteins (using standard    immunofluorescent staining techniques) or a fluorescent ligand that    binds a membrane protein. This strategy can serve a dual purpose in    that, in addition to identifying the neuron shape and processes, it    can also be used to specifically and selectively identify neurons    from a mixed brain culture. Examples of neuron specific markers that    are on the membrane are the various neurotrophic factors. For    example, indirect immunofluorescence against the ciliary    neurotrophic factor CNTF on the surface of neurons can delineate the    architecture of the neuron.-   (3) Staining of Cellular Proteins: Certain cytoplasmic stains label    cellular proteins, some of which are specific to neurons. This    category includes cytoskeletal proteins that help delineate neurons.    Example of this include, but are not limited to: indirect    immunofluorescence against neurofilaments, or against βIII-tubulin,    both which are neuron-specific cytoskeletal proteins.-   (4) A combination of all of these staining strategies can be used to    better identify the neuronal processes and outgrowing neurites.    Identification of Compounds that Stimulate Neurite Outgrowth

Cells are plated onto a substrate, which can be made of any opticallyclear material, including but not limited to glass, plastic, or siliconwafer, such as a conventional light microscope coverslip. In certainsituations, a plastic substrate is sufficient for good attachment of thecells. However, for some cell types, the substrate needs to be coatedwith specific extracellular matrices for good attachment and growth. Forexample, PC12 cells need to be grown on a collagen substrate. Thecompound(s) to be tested are then added to the cells. After theappropriate amount of time the neuronal cells are luminescently labeled(if they were not previously labeled) and then images are acquired andanalyzed automatically to quantify neurite outgrowth, as describedbelow. In some experiments done with PC12 cells treated with NerveGrowth Factor (NGF), the cells were luminescently labeled, imaged, andanalyzed two to seven days after NGF treatment.

Identification of Compounds that Inhibit Neurite Outgrowth

The neuronal cells are first plated onto a substrate as above. The cellsare treated with the compound to be tested and with a control compound(such as Nerve Growth Factor (NGF)) that is known to stimulate neuriteoutgrowth, wherein treatment with the control compound is done eitherbefore, after, or simultaneously with test compound treatment. After anappropriate time period, images are acquired and analyzed automaticallyto quantify neurite outgrowth, as described below.

Identification of Conditions that are Toxic to Neurons and Neurites

The neuronal cells are first plated onto a substrate as above, andtreated to allow neurite outgrowth. For example, the cells could becontacted with NGF, as described above. After neurite outgrowth occurs,the cells are treated with the condition to be tested for toxicitytowards neurons and neurites. Examples of such conditions could beaddition of a concentration range of a potentially toxic compound,alteration of a physical parameter critical to the cells' growth, or insome cases, withdrawal of the factor that stimulates neurite outgrowth,such as NGF. After an appropriate time period images are acquired andanalyzed automatically, as described below, to quantify the neuriteoutgrowth.

Image Acquisition and Analysis

When neuronal cells are sparse or do not have a large degree of neuriteoutgrowth, individual cells can be easily identified. However, asneurites start to grow and the cells start putting out numerousprocesses, these processes may intersect and the neuronal cells becomepart of a large cluster of cells. Thus, the entire cell cluster becomesa single connected luminescent entity. The different processes andstructures that grow from a neuron's cell body include axons, dendrites,neurites, intermediate segments, terminal segments, filopodia and growthcones. For image acquisition and analysis, all of the processes andstructures are classified into two groups: (1) the cell body (also knownas soma), and (2) the neurites. The cell body is the central part of theneuron that contains the nucleus and has a roughly compact, roundmorphology. All of the outgrowths and processes emerging from the cellbody are classified as neurites. A neurite may branch, intersect otherneurites or have smaller processes growing from it, all of which areconsidered as part of their parent neurite for the purpose of imageanalyses. Thus, a neurite has one origin, which is in the cell body, butmay have multiple end points if it branches. The results obtained fromapplying the present method allow the user to define and classify theneurites according to their classification guidelines. For example, inone publication, axons are defined as the longest continuous neuritefrom the cell body, neurite segments between 0.7 μm and 5.1 μm in lengthare defined as filopodia, and those longer than 5.1 μm are calledneurites if emerging from the cell body or terminal segments if an endis attached to a neurite (Ramakers et al, 1998, Developmental BrainResearch, 108:205-216.

The neurite outgrowth methods of the present invention perform thefollowing types of analyses:

-   -   a. Identify the cells' nuclei. If the sample is a mixed culture        of cells, it identifies the nuclei which belong to neurons. The        nuclei are used to identify and keep count of the neurons, and        also to determine the number of cell bodies in a cluster of        neurons;    -   b. Identify the degree of neurite outgrowth in the well and for        the individual cell clusters (if the cells are sparse or neurite        outgrowth is limited, the cell clusters would only consist of        one cell). This is achieved by measuring the morphology of the        neuronal cells (or cell clusters), which includes the cell body        and the neurites extending from them;    -   c. Measure specific properties and morphological features of the        neurites such as their lengths, number, and branch points;    -   d. Measure which and how many of the neurons can be considered        positive for neurite outgrowth; and/or    -   e. Combine the analysis with other HCS analyses on the same        cells or cell clusters. Examples of other HCS assays that can be        applied include, but are not limited to assays for cell        viability, apoptosis, or GPCR and other receptor        internalization.

For example, in one embodiment of the method, the following features ofthe cells, neurons and neurites are measured and reported: TABLE 2 ListOf Output Features Reported By The Current Version Of The NeuriteOutgrowth Method. Parameter Units Description Neurite Outgrowth %Percentage of neurons that are positive for neuiite outgrowth Index(i.e. percentage of neurons whose summed neurite lengths are greaterthan a user entered minimum length threshold). Degree of OutgrowthNumber The neuron's form factor is used as a measure of the degree ofneurite outgrowth. The form factor is the square of the cell'sperimeterdividedby 4π times its area. Itis 1 fora circle, a littlelarger than 1 for cells without outgrowth, and much larger for cellswith significant outgrowth and branching. This parameter is influencedby the number of neurites, their lengths, as well as their branching.The reported parameter is the mean form factor for all identifiedneurons and unresolved neuronal clusters. Total Cells Counted NumberTotal number of cells determined from the nuclear stain (such as Hoechst33342) Number of Neurons Number Number of neurons. A cell is identifiedas a neuron if the intensity of the neuronal stain colocalized with adilated nuclear mask is greater than a user entered minimum intensitythreshold. Number of Positive Number Number of positive neurons.Positive neurons are neurons Neurons whose summed neurite lengths aregreater than a user entered minimum length threshold. Number of NeuritesNumber Number of neurites from positive neurons normalized by the perPositive Neuron number of positive neurons. Neurite Length per μmNeurite length per positive neuron. Sum of neunte lengths from PositiveNeuron positive neurons normalized by the number of positive neurons.Neurite Length per μm Neurite length per neurite. Sum of neurite lengthsfrom positive Neurite neurons normalized by the number of neurites frompositive neurons

In addition, the above features can be combined (such as to normalizeone feature with the other, or to correlate two or more features) to bereported as new features.

A preferred method to quantify neurite outgrowth and measure thesefeatures is described below. As used therein, the following terms havethe given meaning:

“Image” refers to a display of pixels that have intensities.

“Pixel” refers to an (x,y) coordinate location within the array, alongwith the associated intensity value.

“Binary Image” refers to an image in which each pixel has an intensityof either 0 or 1. This is usually derived from an image whose pixelshave a full intensity range. Binarization assigns those pixels with anintensity above a threshold to have an intensity of 1 in the binaryimage. The pixels that have intensities less than or equal to thethreshold have intensity 0 in the binary image. The pixels “containedin” a binary image are considered merely to be the pixels that havevalue 1. The binarized image can also be used as a mask to be applied toother images to measure the intensities of the pixels that arecolocalized with the binary masked structures.

“Thresholding” refers to the process of selecting those pixels of animage whose intensity lie above a value termed a threshold. The resultof thresholding is stored within a binary image wherein pixels above thethreshold have value 1 and the others have value 0.

“Autohresholding” refers to the process of automatically selecting andapplying a suitable threshold value for an image by considering thebrightness distribution present in the image. A variety of differentmethods of selecting the threshold are known; the one used in this assayis known as the “isodata method”, but other autothresholding schemes canbe used.

Connected Component: Any pixel (whose location is not along the imageboundary) has 8 neighboring pixels (4 pixels with which it shares aside, and 4 others with which it shares a corner). A pixel is said to be8-connected to each of its 8 neighboring pixels. “8-connectedcomponents” is a method of determining which of the pixels that haveintensities above an intensity threshold are connected and belong to thesame object. In an 8-connected component scheme, if any of the 8 pixelssurrounding the pixel of interest have intensities above the intensitythreshold, it is identified as part of the same object as the centralpixel. Consider the pixels which have intensity 1 in a binary image.These pixels may be divided into separate groups where the separategroups satisfy certain properties: 1) no group contains a pixel that is8-connected to any pixel of any other group. 2) any two pixels within agroup contain a path connecting them that passes through only pixels ofthat group. The groups satisfying these properties are termed connectedcomponents of the image.

The “Form-Factor” can be used as a quantitative measure of neuriteoutgrowth. It consists of the square of the image object's (e.g. cell orcell cluster) perimeter divided by four times π times the area of theobject. (i.e. FF=perimeter²/(4π Area))

If no neurite outgrowth has occurred and the neuronal cell's shape issimilar to a circle, the Form Factor will be close to 1. As neuriteoutgrowth occurs and the cell or cell cluster becomes more branched, thevalue of this FF measure increases. The average FF over the entireimaged field can be computed to give the degree of neurite outgrowthover the whole well. In addition, the degree of neurite outgrowth forindividual neurons or neuronal-cell clusters can also be determined bytheir individual FF.

Background Compensation: In order to avoid sensitivity from unevenfluorescence distribution, a background compensation filter can beapplied to the image. This stage removes low spatial frequencyvariations from the image. One strategy of doing this is to subtract thebackground intensity from a neighborhood around each pixel. In order toestimate the background intensity in the neighborhood of a pixel, weaverage the intensity within a square region centered upon the pixel.Since we do not want to use very bright pixels to form this estimate(very bright pixels are clearly foreground pixels and should not beincluded in an estimate of the background), we include only pixels lyingbelow some intensity threshold to form the average. Having obtained thebackground intensity estimate, we subtract this intensity from the pixelintensity. The result, when this operation is performed over the entireimage, is a background compensated image.

Branch Identification: A branch is a point when a neurite growing fromthe main cell body splits into more than one (usually two) neuritesegments growing from the neurites. The branch-point or triple-point isthe junction where a single branch splits into two or multiple branches.The image is analyzed to find and count branch points.

Image Acquisition

a. Preferred Embodiment (See FIG. 25A-B)

Inputs to the Method:

Two images are provided as input to the method: a nuclear channel imageand a neurite channel image. In the nuclear channel image, the cells'nuclei are labeled with Hoechst 33342 or some other fluorescent orluminescent nuclear stain. In the neurite channel image, the neuronalcell body, and its attached neurites are fluorescently or luminescentlylabeled.

Initialization Phase:

The initialization phase commences with an optional backgroundcompensation on both the nucleus and neuron images. The backgroundcompensation stage is applied in order to reduce the effect of unevenillumination and to improve detection.

A binary image is generated for both the nuclear channel image and theneurite channel image by application of a threshold; auto-thresholdingis the preferred method as it does not require user input.

Nuclear Channel:

A binary image is generated from the nuclear channel image by theapplication of an auto-threshold. One connected component is present inthis kernel image per neuronal nucleus or nuclear clump. The locationcoordinate of each nucleus is determined by first applying the binarykernel image as a mask over the background-compensated nuclear image,and then using a peak-detection routine to select the pixel which hasthe peak maximum intensity. This pixel is tagged as the positioncoordinate for each nucleus.

Neurite Channel:

A binary reservoir image is generated from the neurite channel image bythe application of an auto-threshold. The pixels in this reservoir imagewill generally be a superset of the pixels in the nuclear kernel image.

Identification of Cell Bodies

The neurons consist of cell bodies with neurites extending from them.Each cell body contains one nucleus, and the cell body covers a largerarea than the nucleus. Before starting to quantify neurite outgrowth,the cell bodies, which are the source of the neurites, need to beidentified. Thus, a series of dilations are performed from each nuclei'speak pixel until the connected components of the kernel image (whichcorrespond to neuronal nuclei) expand to fill out the associatedneuronal cell bodies. The dilations performed are termed conditionaldilations; each time the dilation is applied, a layer of one pixel isadded to the kernel on the condition that the pixels in that layer arepresent in the neuron reservoir image. This means that the increase inarea due to the dilation has still not extended beyond the cell body'sboundaries. During each dilation, the numbers nfront and nadded aremeasured for each connected component in the kernel image. Nfront is thenumber of pixels that would be added to the connected component by asimple (unconditional) dilation, which is just dilation by an additionalpixel. Nfront can be thought of as the new perimeter, measured in numberof pixels, of the object due to the latest dilation. Nadded is thenumber of pixels that are actually added by the conditionaldilation—conditional because after a one pixel dilation, only thosepixels in the new perimeter which are positive in the reservoir imageare counted. Thus, nadded is the number of pixels in the new perimeterwhich has an intensity of 1 in the binary reservoir image. If the rationadded/nfront is computed to be less than some user-defined numberthreshold in the course of a dilation (we find that a range from 0.05 to0.3 empirically works with our test images), no more dilations areperformed on that connected component. This means that the extent of thecell body has been reached, and no more dilations are required. Theadditional pixels in subsequent dilations that are positive in thebinary reservoir image belong to actual neurites growing out from thecell body. The extent of the cell body can be reported as the cell bodyarea. When all connected components have reached this stage (i.e. allthe individual nuclei have been processed to this stage), then the nextstep of the method is initiated.

At this point, the kernel image contains one connected component (i.e.one entity) for each neuronal cell body.

Iteration Phase:

The next step is to identify the neurites extending from each cell body.For this, one conditional dilation is performed on the kernel image inorder to identify each neurite stub. The term dilation image describesthe image containing only the positive binary pixels added by adilation. Each connected component in the dilation image is termed anode. Each node is used to initialize a one-node neurite data structure.A neurite data structure is intended to represent the physical neuriteas it extends outward from the neuronal cell body, potentiallycontaining multiple branches and potentially joining with otherneurites.

Next, conditional dilations are successively performed upon the kernelimage until no further pixels from the reservoir image remain that arecontiguous to pixels of the kernel image. In the dilation image producedby each such dilation, the set of nodes is computed. Each noderepresents either the continuation of a neurite object, a branching of aneurite object, or the joining of two neurite objects. An association isformed between a node and an existing neurite object if one or morepixels of a node are adjacent to the pixels of the neurite object. If anode is associated with more than one neurite object, then it representsa join point. If multiple nodes are associated with a neurite object,then it represents a branch point. If a node is associated with just oneneurite object and that neurite object is associated only with the saidnode, then the node is an extension of the neurite object. Theextension, branch or join is recorded. In the case of joins, the neuriteobjects involved are merged.

The entire neurite is identified by linking together its set ofconnected nodes, and then the neurite's length is measured. Lengththreshold criteria may be applied to classify the different neurites.One application of such criteria would be to reject neurites that aretoo short. Each neurite origin is associated with the neuron itoriginated from. One way of doing this is to link the neurite's originnode with either the nearest cell body or nuclear peak. In certain celltypes (e.g. PC12 cells), the neurons form clusters and only a subset ofcells within the cluster extend neurites. This association of neuriteswith their originating neurons identifies the neurites and theiroriginating cells within a cluster of cells.

Output Features:

A variety of different quantities can be measured by this method. First,the number of cells and the number of neurons can be measured andreported. For each neurite, the total length (measured as the sum of thelengths of all its branches) and number of branches can be measured. Foreach nucleus, the number of neurites that emerge from it can bemeasured. For each cluster, the form-factor (perimeter²÷(4π×area)) ismeasured and reported as the degree of neurite outgrowth. In addition,the neurite lengths from each nuclei are summed, and if greater than alength threshold, the nuclei are identified as being positive forneurite outgrowth. These measures can be combined in different ways togive the output features reported in Table 2.

Validation of Preferred Embodiment

1. Measurement of Neurite Outgrowth in PC6-3 Cells

PC6-3 cells (a sub-clone of PC12 cells) were grown on 96-wellmicroplates whose wells had been coated with collagen. The wellscontained different concentrations of NGF (nerve growth factor) (0-1000ng/ml) to stimulate neurite outgrowth. A control population did notcontain NGF. After two days, the cells were fixed and indirectimmunofluorescence was performed against βIII-tubulin, using a rabbitanti-βIII-tubulin primary antibody and an ALEXAFLUOR™ 488 conjugatedgoat anti-rabbit secondary antibody (Molecular Probes). The cells werethen fixed in 3.7% formaldehyde for 20 minutes, and the fixativesolution also contained 10 μg/ml Hoechst 33342 to label their nuclei.The cells were imaged on the cell screening system of the presentinvention and then analyzed with a prototype method described above.Results given below are for the form-factor and mean neurite length as afunction of NGF concentration: NGF Concentration (ng/ml) Mean NeuriteLength (μm) Mean Form Factor 0 3.8 2.5 62.5 27.8 16.3 250 47.6 41.5 100064.4 51.72. Measurement of Dopamine Toxicity to Neurites from PC12 Cells

PC12 cells were grown for 7 days in the presence of 1 μg/ml NGF on 96well microplates with collagen-IV coated wells. Varying concentrationsof dopamine were added for 3 hours before the cells were fixed in 3.7%formaldehyde for 20 minutes; the fixative solution also contained 10μg/ml Hoechst 33342. The cells were stained by indirectimmunofluorescence using a rabbit primary antibody against βIII-tubulin,and an ALEXAFLUOR™ 488 conjugated goat anti-rabbit secondary antibody.The cells were imaged on the cell screening system of the presentinvention, and then analyzed with the prototype method described above.Results given below are for the Neurite Outgrowth Index (see Table 2) asa function of dopamine concentration. Each data point is the mean resultfrom 8 wells, and error bars are the standard deviations. The IC₅₀ (50%inhibitory concentration) for dopamine toxicity to neurites from thisdata is 0.46 mM. Neurite Outgrowth Index (%) Dopamine Concentration (mM)(mean +/− standard deviation) 0.0 46 +/− 5 0.05 43 +/− 4 0.1 37 +/− 30.2 37 +/− 3 0.4 25 +/− 3 0.8 17 +/− 2 1.6 11 +/− 2

b. Alternative Image Acquisition Embodiment (See FIGS. 26 and 27A-B)

In an alternative embodiment, the method measures the percentage ofcells in a field that are in a particular state, in this case, thosethat are neurons in a culture containing a mixed population of celltypes. A Positive State means that the cell is brightly fluorescent, anda Negative State means that the cell has little or no fluorescence. Whena neuron-specific reporter molecule is used, a Positive State occurs forevery neuronal cell, and a Negative State for all other cells. Toidentify neurons, two images are captured per field as discussed above.The number of cells in a Positive State is compared to the total numberof all cells to obtain the percentage of Positive State cells in afield.

Furthermore, a mixture of different types of neurons can be assayed forneurite outgrowth. Each neuronal sub-population to be analyzed isidentified by a distinct reporter molecule. Such a method can be used,for example, to distinguish GABAnergic neurons from cholinergic neuronsin a mixed population, by immunofluorescence against the specificneurotransmitters' receptor.

This alternative embodiment can be summarized as follows:

Detection Threshold Computation

Two control wells are used: a sample where all the cells are in thePositive State, and a sample where all cells are in the Negative State.The Positive State cells are brightly labeled and the Negative Statecells are not. In order to improve cell segmentation, all images can bebackground compensated by subtracting the local average intensity over auser determined area. For the negative control, a threshold is set tominimize the variance of the intensity distributions of the non-cellbackground and the cells. For the positive control, a threshold is setto minimize the variance of the intensity distributions of the non-cellbackground and the cells. The Positive State detection threshold is setas a weighted sum of the thresholds computed from the control images.

Detection and Counting of Nuclei (Hoechst Labeled)

The nuclear image is background compensated by subtraction of localaverage. A threshold is applied to the image. The image has a bimodalintensity distribution due to the dim pixels from the non-cellbackground and the brighter pixels associated with cells. The thresholdis set to minimize the variance of these two distributions. 8-Connectedcomponents are labeled and counted. This identifies the area covered byeach nucleus, and sets each individual nucleus's mask.

Detection and Count of Positive State

The 8-connected components of the nucleus mask image are labeled. Theimage where Positive State cells are luminescently labeled is backgroundcompensated by subtraction of the local average. Positive State cellsare then selected by means of a fixed or autothresholding (selection ofpixels above Positive State detection threshold). The positive cells arethen identified by either the “Morphological” or “Blob Analysis” method:

-   -   a. Morphological method (FIG. 28): A morphological dilation (of        5 pixels for example) is applied to the selected areas. The        selected area is logically “AND”ed with the nucleus mask and        then the 8-connected components of the resulting area are        labeled and counted.    -   b. Blob Analysis Method (FIG. 29): The selected area is        logically “AND”ed with each separate 8-connected component of        the nucleus mask. The area of the resulting image is compared        with a threshold (rejection threshold), and if larger, the cell        is counted as Positive State.        Linking Positive State Cells (e.g. neurons) to Neurite Outgrowth        Assays

For each well the number of detected nuclei and the number of nuclei inthe Positive State (i.e. that are neurons) are saved and reported. Thetotal integrated intensity and the average intensity per pixel can alsobe reported. Next, the neurite outgrowth methods are applied to thePositive State neuronal cells to quantify and characterize their neuriteoutgrowth. The Positive State nuclei are used to index and track thePositive State cells.

Measuring Degree of Neurite Outgrowth

To measure the degree of neurite outgrowth, both the perimeter and thearea of the neuronal cell or cell cluster are measured. To quantify thedegree of neurite outgrowth, we use the Form Factor (FF), as discussedabove. A summary of the series of steps involved is as follows:

-   1. Background Compensation: Same as in preferred embodiment.-   2. Image Binarization: The image is then binarized to generate a    mask image with all the selected cells. The skeleton of the mask is    then also computed.-   3. Degree of Outgrowth: Connected components in the binarized image    are labeled, each of them representing an individual cell or a cell    cluster. The perimeter, area, and form factor of each component is    computed.-   4. Branch Identification: To compute all the branches, first the    cell branches are removed by applying a morphological opening (e.g.    an image processing erosion of the image) to the original mask    image. Then, from the skeletonized mask image (computed above) the    region's main cell bodies are subtracted. This leaves only the    skeleton of cell branches.-   5. Triple-Point Identification: A triple point is the junction where    a single branch splits into two or multiple branches, or different    neurite branches intersect. This image is analyzed to find and count    triple points. These points are then removed from the image, thus    separating each branch and its sub-branches. A connected components    labeling is used to count the number of branches and sub-branches    and, by counting the number of pixels of each object (branch), the    length of each separate branch is also computed.

Triple Point Characterization: Image acquisition can be expanded toinclude a feature that further characterizes the triple points. Asmentioned above, the triple points may be places where neurites fromdifferent cells intersect. If a connection is made between thesedifferent neurites, certain proteins that are characteristic of theseconnections may be expressed. Examples may be synaptic vesicle proteinssuch as synaptobrevin. Immunofluorescence against these proteins using afluorophore with a spectra distinguishable from other used in the assayallows determination of whether a connection has been made. Comparisonwith the neuronal luminescent label to determine whether a triple pointis indeed co-localized with the immunofluorescence against the proteincharacterizes the triple point and measures and quantifies whetherinter-neurite connections are being made.

Validation Data Using the Alternative Image Acquisition Embodiment

1. Measurement of Neurite Outgrowth in PC12 Cells

PC12 cells were grown on 96-well microplates whose wells had been coatedwith collagen. Some of the wells contained NGF (nerve growth factor)(0.5-1 μg/ml) to stimulate neurite outgrowth. A control population didnot contain NGF. After two days, the cells were labeled with CMFDAaccording to the manufacturer's instructions. The cells were then fixedin 3.7% formaldehyde for 10 minutes, and the fixative solution alsocontained 10 μg/ml Hoechst 33342 to label their nuclei. The cells wereimaged on the cell screening system of the present invention and thenanalyzed with a prototype method described above. First, the cells FromFactors were calculated. Condition Mean form factor +/− sem +NGF 18.43+/− 1 4.57 −NGF  1.33 +/− 0.05

The results from applying the neurite-outgrowth method to a cluster ofcells that had been treated with NGF returned the following analysis foron cell cluster: Property Result Number of cell bodies 3 Degree ofneurite outgrowth (form factor) 70.24 # neurites and neurite segments 5# branch points (i.e.: triple points) 5 Neurite segment length (in μm)29, 44, 67, 78, and 92

EXAMPLE 11 Additional Screens

Translocation Between the Plasma Membrane and the Cytoplasm:

Profilactin complex dissociation and binding of profilin to the plasmamembrane. In one embodiment, a fluorescent protein biosensor of profilinmembrane binding is prepared by labeling purified profilin (Federov etal. (1994), J. Molec. Biol. 241:480-482; Lanbrechts et al. (1995), Eur.J. Biochem. 230:281-286) with a probe possessing a fluorescence lifetimein the range of 2-300 ns. The labeled profilin is introduced into livingindicator cells using bulk loading methodology and the indicator cellsare treated with test compounds. Fluorescence anisotropy imagingmicroscopy (Gough and Taylor (1993), J. Cell Biol. 121:1095-1107) isused to measure test-compound dependent movement of the fluorescentderivative of profilin between the cytoplasm and membrane for a periodof time after treatment ranging from 0.1 s to 10 h.

Rho-RhoGDI complex translocation to the membrane. In another embodiment,indicator cells are treated with test compounds and then fixed, washed,and permeabilized. The indicator cell plasma membrane, cytoplasm, andnucleus are all labeled with distinctly colored markers followed byimmunolocalization of Rho protein (Self et al. (1995), Methods inEnzymology 256:3-10; Tanaka et al. (1995), Methods in Enzymology256:41-49) with antibodies labeled with a fourth color. Each of the fourlabels is imaged separately using the cell screening system, and theimages used to calculate the amount of inhibition or activation oftranslocation effected by the test compound. To do this calculation, theimages of the probes used to mark the plasma membrane and cytoplasm areused to mask the image of the immunological probe marking the locationof intracellular Rho protein. The integrated brightness per unit areaunder each mask is used to form a translocation quotient by dividing theplasma membrane integrated brightness/area by the cytoplasmic integratedbrightness/area. By comparing the translocation quotient values fromcontrol and experimental wells, the percent translocation is calculatedfor each potential lead compound.

β-Arrestin Translocation to the Plasma Membrane Upon G-Protein ReceptorActivation.

In another embodiment of a cytoplasm to membrane translocationhigh-content screen, the translocation of β-arrestin protein from thecytoplasm to the plasma membrane is measured in response to celltreatment. To measure the translocation, living indicator cellscontaining luminescent domain markers are treated with test compoundsand the movement of the β-arrestin marker is measured in time and spaceusing the cell screening system of the present invention. In a preferredembodiment, the indicator cells contain luminescent markers consistingof a green fluorescent protein β-arrestin (GFP-β-arrestin) proteinchimera (Barak et al. (1997), J. Biol. Chem. 272:27497-27500; Daaka etal. (1998), J. Biol. Chem. 273:685-688) that is expressed by theindicator cells through the use of transient or stable cell transfectionand other reporters used to mark cytoplasmic and membrane domains. Whenthe indicator cells are in the resting state, the domain markermolecules partition predominately in the plasma membrane or in thecytoplasm. In the high-content screen, these markers are used todelineate the cell cytoplasm and plasma membrane in distinct channels offluorescence. When the indicator cells are treated with a test compound,the dynamic redistribution of the GFP-β-arrestin is recorded as a seriesof images over a time scale ranging from 0.1 s to 10 h. In a preferredembodiment, the time scale is 1 h. Each image is analyzed by a methodthat quantifies the movement of the GFP-β-arrestin protein chimerabetween the plasma membrane and the cytoplasm. To do this calculation,the images of the probes used to mark the plasma membrane and cytoplasmare used to mask the image of the GFP-β-arrestin probe marking thelocation of intracellular GFP-β-arrestin protein. The integratedbrightness per unit area under each mask is used to form a translocationquotient by dividing the plasma membrane integrated brightness/area bythe cytoplasmic integrated brightness/area. By comparing thetranslocation quotient values from control and experimental wells, thepercent translocation is calculated for each potential lead compound.The output of the high-content screen relates quantitative datadescribing the magnitude of the translocation within a large number ofindividual cells that have been treated with test compounds of interest.

Translocation Between the Endoplasmic Reticulum and the Golgi:

In one embodiment of an endoplasmic reticulum to Golgi translocationhigh-content screen, the translocation of a VSVG protein from the ts045mutant strain of vesicular stomatitis virus (Ellenberg et al. (1997), J.Cell Biol. 138:1193-1206; Presley et al. (1997) Nature 389:81-85) fromthe endoplasmic reticulum to the Golgi domain is measured in response tocell treatment. To measure the translocation, indicator cells containingluminescent reporters are treated with test compounds and the movementof the reporters is measured in space and time using the cell screeningsystem of the present invention. The indicator cells contain luminescentreporters consisting of a GFP-VSVG protein chimera that is expressed bythe indicator cell through the use of transient or stable celltransfection and other domain markers used to measure the localizationof the endoplasmic reticulum and Golgi domains. When the indicator cellsare in their resting state at 40° C., the GFP-VSVG protein chimeramolecules are partitioned predominately in the endoplasmic reticulum. Inthis high-content screen, domain markers of distinct colors used todelineate the endoplasmic reticulum and the Golgi domains in distinctchannels of fluorescence. When the indicator cells are treated with atest compound and the temperature is simultaneously lowered to 32° C.,the dynamic redistribution of the GFP-VSVG protein chimera is recordedas a series of images over a time scale ranging from 0.1 s to 10 h. Eachimage is analyzed by a method that quantifies the movement of theGFP-VSVG protein chimera between the endoplasmic reticulum and the Golgidomains. To do this calculation, the images of the probes used to markthe endoplasmic reticulum and the Golgi domains are used to mask theimage of the GFP-VSVG probe marking the location of intracellularGFP-VSVG protein. The integrated brightness per unit area under eachmask is used to form a translocation quotient by dividing theendoplasmic reticulum integrated brightness/area by the Golgi integratedbrightness/area. By comparing the translocation quotient values fromcontrol and experimental wells, the percent translocation is calculatedfor each potential lead compound. The output of the high-content screenrelates quantitative data describing the magnitude of the translocationwithin a large number of individual cells that have been treated withtest compounds of interest at final concentrations ranging from 10⁻¹² Mto 10⁻³ M for a period ranging from 1 min to 10 h.

High-Content Screens Involving the Functional Localization ofMacromolecules

Within this class of high-content screen, the functional localization ofmacromolecules in response to external stimuli is measured within livingcells.

Glycolytic enzyme activity regulation. In a preferred embodiment of acellular enzyme activity high-content screen, the activity of keyglycolytic regulatory enzymes are measured in treated cells. To measureenzyme activity, indicator cells containing luminescent labelingreagents are treated with test compounds and the activity of thereporters is measured in space and time using cell screening system ofthe present invention.

In one embodiment, the reporter of intracellular enzyme activity isfructose-6-phosphate, 2-kinase/fructose-2,6-bisphosphatase (PFK-2), aregulatory enzyme whose phosphorylation state indicates intracellularcarbohydrate anabolism or catabolism (Deprez et al. (1997) J. Biol.Chem. 272:17269-17275; Kealer et al. (1996) FEBS Letters 395:225-227;Lee et al. (1996), Biochemistry 35:6010-6019). The indicator cellscontain luminescent reporters consisting of a fluorescent proteinbiosensor of PFK-2 phosphorylation. The fluorescent protein biosensor isconstructed by introducing an environmentally sensitive fluorescent dyenear to the known phosphorylation site of the enzyme (Deprez et al.(1997), supra; Giuliano et al. (1995), supra). The dye can be of theketocyanine class (Kessler and Wolfbeis (1991), Spectrochimica Acta47A:187-192) or any class that contains a protein reactive moiety and afluorochrome whose excitation or emission spectrum is sensitive tosolution polarity. The fluorescent protein biosensor is introduced intothe indicator cells using bulk loading methodology.

Living indicator cells are treated with test compounds, at finalconcentrations ranging from 10⁻¹² M to 10⁻³ M for times ranging from 0.1s to 10 h. In a preferred embodiment, ratio image data are obtained fromliving treated indicator cells by collecting a spectral pair offluorescence images at each time point. To extract morphometric datafrom each time point, a ratio is made between each pair of images bynumerically dividing the two spectral images at each time point, pixelby pixel. Each pixel value is then used to calculate the fractionalphosphorylation of PFK-2. At small fractional values of phosphorylation,PFK-2 stimulates carbohydrate catabolism. At high fractional values ofphosphorylation, PFK-2 stimulates carbohydrate anabolism.

Protein kinase A activity and localization of subunits. In anotherembodiment of a high-content screen, both the domain localization andactivity of protein kinase A (PKA) within indicator cells are measuredin response to treatment with test compounds.

The indicator cells contain luminescent reporters including afluorescent protein biosensor of PKA activation. The fluorescent proteinbiosensor is constructed by introducing an environmentally sensitivefluorescent dye into the catalytic subunit of PKA near the site known tointeract with the regulatory subunit of PKA (Harootunian et al. (1993),Mol. Biol. of the Cell 4:993-1002; Johnson et al. (1996), Cell85:149-158; Giuliano et al. (1995), supra). The dye can be of theketocyanine class (Kessler, and Wolfbeis (1991), Spectrochimica Acta47A:187-192) or any class that contains a protein reactive moiety and afluorochrome whose excitation or emission spectrum is sensitive tosolution polarity. The fluorescent protein biosensor of PKA activationis introduced into the indicator cells using bulk loading methodology.

In one embodiment, living indicator cells are treated with testcompounds, at final concentrations ranging from 10⁻¹² M to 10⁻³ M fortimes ranging from 0.1 s to 10 h. In a preferred embodiment, ratio imagedata are obtained from living treated indicator cells. To extractbiosensor data from each time point, a ratio is made between each pairof images, and each pixel value is then used to calculate the fractionalactivation of PKA (e.g., separation of the catalytic and regulatorysubunits after cAMP binding). At high fractional values of activity,PFK-2 stimulates biochemical cascades within the living cell.

To measure the translocation of the catalytic subunit of PKA, indicatorcells containing luminescent reporters are treated with test compoundsand the movement of the reporters is measured in space and time usingthe cell screening system. The indicator cells contain luminescentreporters consisting of domain markers used to measure the localizationof the cytoplasmic and nuclear domains. When the indicator cells aretreated with a test compounds, the dynamic redistribution of a PKAfluorescent protein biosensor is recorded intracellularly as a series ofimages over a time scale ranging from 0.1 s to 10 h. Each image isanalyzed by a method that quantifies the movement of the PKA between thecytoplasmic and nuclear domains. To do this calculation, the images ofthe probes used to mark the cytoplasmic and nuclear domains are used tomask the image of the PKA fluorescent protein biosensor. The integratedbrightness per unit area under each mask is used to form a translocationquotient by dividing the cytoplasmic integrated brightness/area by thenuclear integrated brightness/area. By comparing the translocationquotient values from control and experimental wells, the percenttranslocation is calculated for each potential lead compound. The outputof the high-content screen relates quantitative data describing themagnitude of the translocation within a large number of individual cellsthat have been treated with test compound in the concentration range of10⁻¹²M to 10⁻³M.

High-Content Screens Involving the Induction or Inhibition of GeneExpression

RNA-Based Fluorescent Biosensors

Cytoskeletal protein transcription and message localization. Regulationof the general classes of cell physiological responses includingcell-substrate adhesion, cell-cell adhesion, signal transduction,cell-cycle events, intermediary and signaling molecule metabolism, celllocomotion, cell-cell communication, and cell death can involve thealteration of gene expression. High-content screens can also be designedto measure this class of physiological response.

In one embodiment, the reporter of intracellular gene expression is anoligonucleotide that can hybridize with the target mRNA and alter itsfluorescence signal. In a preferred embodiment, the oligonucleotide is amolecular beacon (Tyagi and Kramer (1996) Nat. Biotechnol. 14:303-308),a luminescence-based reagent whose fluorescence signal is dependent onintermolecular and intramolecular interactions. The fluorescentbiosensor is constructed by introducing a fluorescence energy transferpair of fluorescent dyes such that there is one at each end (5′ and 3′)of the reagent. The dyes can be of any class that contains a proteinreactive moiety and fluorochromes whose excitation and emission spectraoverlap sufficiently to provide fluorescence energy transfer between thedyes in the resting state, including, but not limited to, fluoresceinand rhodamine (Molecular Probes, Inc.). In a preferred embodiment, aportion of the message coding for β-actin (Kislauskis et al. (1994), J.Cell Biol. 127:441-451; McCann et al. (1997), Proc. Natl. Acad. Sci.94:5679-5684; Sutoh (1982), Biochemistry 21:3654-3661) is inserted intothe loop region of a hairpin-shaped oligonucleotide with the endstethered together due to intramolecular hybridization. At each end ofthe biosensor a fluorescence donor (fluorescein) and a fluorescenceacceptor (rhodamine) are covalently bound. In the tethered state, thefluorescence energy transfer is maximal and therefore indicative of anunhybridized molecule. When hybridized with the mRNA coding for β-actin,the tether is broken and energy transfer is lost. The completefluorescent biosensor is introduced into the indicator cells using bulkloading methodology.

In one embodiment, living indicator cells are treated with testcompounds, at final concentrations ranging from 10⁻¹² M to 10⁻³ M fortimes ranging from 0.1 s to 10 h. In a preferred embodiment, ratio imagedata are obtained from living treated indicator cells. To extractmorphometric data from each time point, a ratio is made between eachpair of images, and each pixel value is then used to calculate thefractional hybridization of the labeled nucleotide. At small fractionalvalues of hybridization little expression of β-actin is indicated. Athigh fractional values of hybridization, maximal expression of β-actinis indicated. Furthermore, the distribution of hybridized moleculeswithin the cytoplasm of the indicator cells is also a measure of thephysiological response of the indicator cells.

Cell Surface Binding of a Ligand

Labeled insulin binding to its cell surface receptor in living cells.Cells whose plasma membrane domain has been labeled with a labelingreagent of a particular color are incubated with a solution containinginsulin molecules (Lee et al. (1997), Biochemistry 36:2701-2708;Martinez-Zaguilan et al. (1996), Am. J. Physiol. 270:C1438-C1446) thatare labeled with a luminescent probe of a different color for anappropriate time under the appropriate conditions. After incubation,unbound insulin molecules are washed away, the cells fixed and thedistribution and concentration of the insulin on the plasma membrane ismeasured. To do this, the cell membrane image is used as a mask for theinsulin image. The integrated intensity from the masked insulin image iscompared to a set of images containing known amounts of labeled insulin.The amount of insulin bound to the cell is determined from the standardsand used in conjunction with the total concentration of insulinincubated with the cell to calculate a dissociation constant or insulinto its cell surface receptor.

Labeling of Cellular Compartments

Whole Cell Labeling

Whole cell labeling is accomplished by labeling cellular components suchthat dynamics of cell shape and motility of the cell can be measuredover time by analyzing fluorescence images of cells.

In one embodiment, small reactive fluorescent molecules are introducedinto living cells. These membrane-permeant molecules both diffusethrough and react with protein components in the plasma membrane. Dyemolecules react with intracellular molecules to both increase thefluorescence signal emitted from each molecule and to entrap thefluorescent dye within living cells. These molecules include reactivechloromethyl derivatives of aminocoumarins, hydroxycoumarins, eosindiacetate, fluorescein diacetate, some Bodipy dye derivatives, andtetramethylrhodamine. The reactivity of these dyes toward macromoleculesincludes free primary amino groups and free sulfhydryl groups.

In another embodiment, the cell surface is labeled by allowing the cellto interact with fluorescently labeled antibodies or lectins (SigmaChemical Company, St. Louis, Mo.) that react specifically with moleculeson the cell surface. Cell surface protein chimeras expressed by the cellof interest that contain a green fluorescent protein, or mutant thereof,component can also be used to fluorescently label the entire cellsurface. Once the entire cell is labeled, images of the entire cell orcell array can become a parameter in high content screens, involving themeasurement of cell shape, motility, size, and growth and division.

Plasma Membrane Labeling

In one embodiment, labeling the whole plasma membrane employs some ofthe same methodology described above for labeling the entire cells.Luminescent molecules that label the entire cell surface act todelineate the plasma membrane.

In a second embodiment subdomains of the plasma membrane, theextracellular surface, the lipid bilayer, and the intracellular surfacecan be labeled separately and used as components of high contentscreens. In the first embodiment, the extracellular surface is labeledusing a brief treatment with a reactive fluorescent molecule such as thesuccinimidyl ester or iodoacetamde derivatives of fluorescent dyes suchas the fluoresceins, rhodamines, cyanines, and Bodipys.

In a third embodiment, the extracellular surface is labeled usingfluorescently labeled macromolecules with a high affinity for cellsurface molecules. These include fluorescently labeled lectins such asthe fluorescein, rhodamine, and cyanine derivatives of lectins derivedfrom jack bean (Con A), red kidney bean (erythroagglutinin PHA-E), orwheat germ.

In a fourth embodiment, fluorescently labeled antibodies with a highaffinity for cell surface components are used to label the extracellularregion of the plasma membrane. Extracellular regions of cell surfacereceptors and ion channels are examples of proteins that can be labeledwith antibodies.

In a fifth embodiment, the lipid bilayer of the plasma membrane islabeled with fluorescent molecules. These molecules include fluorescentdyes attached to long chain hydrophobic molecules that interact stronglywith the hydrophobic region in the center of the plasma membrane lipidbilayer. Examples of these dyes include the PKH series of dyes (U.S.Pat. Nos. 4,783,401, 4,762,701, and 4,859,584; available commerciallyfrom Sigma Chemical Company, St. Loius, Mo.), fluorescent phospholipidssuch as nitrobenzoxadiazole glycerophosphoethanolamine andfluorescein-derivatized dihexadecanoylglycerophosphoetha-nolamine,fluorescent fatty acids such as5-butyl-4,4-difluoro-4-bora-3a,4a-diaza-s-indacene-3-nonanoic acid and1-pyrenedecanoic acid (Molecular Probes, Inc.), fluorescent sterolsincluding cholesteryl4,4-difluoro-5,7-dimethyl-4-bora-3a,4a-diaza-s-indacene-3-dodecanoateand cholesteryl 1-pyrenehexanoate, and fluorescently labeled proteinsthat interact specifically with lipid bilayer components such as thefluorescein derivative of annexin V (Caltag Antibody Co, Burlingame,Calif.).

In another embodiment, the intracellular component of the plasmamembrane is labeled with fluorescent molecules. Examples of thesemolecules are the intracellular components of the trimeric G-proteinreceptor, adenylyl cyclase, and ionic transport proteins. Thesemolecules can be labeled as a result of tight binding to a fluorescentlylabeled specific antibody or by the incorporation of a fluorescentprotein chimera that is comprised of a membrane-associated protein andthe green fluorescent protein, and mutants thereof.

Endosome Fluorescence Labeling

In one embodiment, ligands that are transported into cells byreceptor-mediated endocytosis are used to trace the dynamics ofendosomal organelles. Examples of labeled ligands include BodipyFL-labeled low density lipoprotein complexes, tetramethylrhodaminetransferrin analogs, and fluorescently labeled epidermal growth factor(Molecular Probes, Inc.)

In a second embodiment, fluorescently labeled primary or secondaryantibodies (Sigma Chemical Co. St. Louis, Mo.; Molecular Probes, Inc.Eugene, Oreg.; Caltag Antibody Co.) that specifically label endosomalligands are used to mark the endosomal compartment in cells.

In a third embodiment, endosomes are fluorescently labeled in cellsexpressing protein chimeras formed by fusing a green fluorescentprotein, or mutants thereof, with a receptor whose internalizationlabels endosomes. Chimeras of the EGF, transferrin, and low densitylipoprotein receptors are examples of these molecules.

Lysosome Labeling

In one embodiment, membrane permeant lysosome-specific luminescentreagents are used to label the lysosomal compartment of living and fixedcells. These reagents include the luminescent molecules neutral red,N-(3-((2,4-dinitrophenyl)amino)propyl)-N-(3-aminopropyl)methylamine, andthe LysoTracker probes which report intralysosomal pH as well as thedynamic distribution of lysosomes (Molecular Probes, Inc.)

In a second embodiment, antibodies against lysosomal antigens (SigmaChemical Co.; Molecular Probes, Inc.; Caltag Antibody Co.) are used tolabel lysosomal components that are localized in specific lysosomaldomains. Examples of these components are the degradative enzymesinvolved in cholesterol ester hydrolysis, membrane protein proteases,and nucleases as well as the ATP-driven lysosomal proton pump.

In a third embodiment, protein chimeras consisting of a lysosomalprotein genetically fused to an intrinsically luminescent protein suchas the green fluorescent protein, or mutants thereof, are used to labelthe lysosomal domain. Examples of these components are the degradativeenzymes involved in cholesterol ester hydrolysis, membrane proteinproteases, and nucleases as well as the ATP-driven lysosomal protonpump.

Cytoplasmic Fluorescence Labeling

In one embodiment, cell permeant fluorescent dyes (Molecular Probes,Inc.) with a reactive group are reacted with living cells. Reactive dyesincluding monobromobimane, 5-chloromethylfluorescein diacetate, carboxyfluorescein diacetate succinimidyl ester, and chloromethyltetramethylrhodamine are examples of cell permeant fluorescent dyes thatare used for long term labeling of the cytoplasm of cells.

In a second embodiment, polar tracer molecules such as Lucifer yellowand cascade blue-based fluorescent dyes (Molecular Probes, Inc.) areintroduced into cells using bulk loading methods and are also used forcytoplasmic labeling.

In a third embodiment, antibodies against cytoplasmic components (SigmaChemical Co.; Molecular Probes, Inc.; Caltag Antibody Co.) are used tofluorescently label the cytoplasm. Examples of cytoplasmic antigens aremany of the enzymes involved in intermediary metabolism. Enolase,phosphofructokinase, and acetyl-CoA dehydrogenase are examples ofuniformly distributed cytoplasmic antigens.

In a fourth embodiment, protein chimeras consisting of a cytoplasmicprotein genetically fused to an intrinsically luminescent protein suchas the green fluorescent protein, or mutants thereof, are used to labelthe cytoplasm. Fluorescent chimeras of uniformly distributed proteinsare used to label the entire cytoplasmic domain. Examples of theseproteins are many of the proteins involved in intermediary metabolismand include enolase, lactate dehydrogenase, and hexokinase.

In a fifth embodiment, antibodies against cytoplasmic antigens (SigmaChemical Co.; Molecular Probes, Inc.; Caltag Antibody Co.) are used tolabel cytoplasmic components that are localized in specific cytoplasmicsub-domains. Examples of these components are the cytoskeletal proteinsactin, tubulin, and cytokeratin. A population of these proteins withincells is assembled into discrete structures, which in this case, arefibrous. Fluorescence labeling of these proteins with antibody-basedreagents therefore labels a specific sub-domain of the cytoplasm.

In a sixth embodiment, non-antibody-based fluorescently labeledmolecules that interact strongly with cytoplasmic proteins are used tolabel specific cytoplasmic components. One example is a fluorescentanalog of the enzyme DNAse I (Molecular Probes, Inc.) Fluorescentanalogs of this enzyme bind tightly and specifically to cytoplasmicactin, thus labeling a sub-domain of the cytoplasm. In another example,fluorescent analogs of the mushroom toxin phalloidin or the drugpaclitaxel (Molecular Probes, Inc.) are used to label components of theactin- and microtubule-cytoskeletons, respectively.

In a seventh embodiment, protein chimeras consisting of a cytoplasmicprotein genetically fused to an intrinsically luminescent protein suchas the green fluorescent protein, or mutants thereof, are used to labelspecific domains of the cytoplasm. Fluorescent chimeras of highlylocalized proteins are used to label cytoplasmic sub-domains. Examplesof these proteins are many of the proteins involved in regulating thecytoskeleton. They include the structural proteins actin, tubulin, andcytokeratin as well as the regulatory proteins microtubule associatedprotein 4 and α-actinin.

Nuclear Labeling

In one embodiment, membrane permeant nucleic-acid-specific luminescentreagents (Molecular Probes, Inc.) are used to label the nucleus ofliving and fixed cells. These reagents include cyanine-based dyes (e.g.,TOTO®, YOYO®, and BOBO™), phenanthidines and acridines (e.g., ethidiumbromide, propidium iodide, and acridine orange), indoles and imidazoles(e.g., Hoechst 33258, Hoechst 33342, and 4′,6-diamidino-2-phenylindole),and other similar reagents (e.g., 7-aminoactinomycin D,hydroxystilbamidine, and the psoralens).

In a second embodiment, antibodies against nuclear antigens (SigmaChemical Co.; Molecular Probes, Inc.; Caltag Antibody Co.) are used tolabel nuclear components that are localized in specific nuclear domains.Examples of these components are the macromolecules involved inmaintaining DNA structure and function. DNA, RNA, histones, DNApolymerase, RNA polymerase, lamins, and nuclear variants of cytoplasmicproteins such as actin are examples of nuclear antigens.

In a third embodiment, protein chimeras consisting of a nuclear proteingenetically fused to an intrinsically luminescent protein such as thegreen fluorescent protein, or mutants thereof, are used to label thenuclear domain. Examples of these proteins are many of the proteinsinvolved in maintaining DNA structure and function. Histones, DNApolymerase, RNA polymerase, lamins, and nuclear variants of cytoplasmicproteins such as actin are examples of nuclear proteins.

Mitochondrial Labeling

In one embodiment, membrane permeant mitochondrial-specific luminescentreagents (Molecular Probes, Inc.) are used to label the mitochondria ofliving and fixed cells. These reagents include rhodamine 123,tetramethyl rosamine, JC-1, and the MitoTracker reactive dyes.

In a second embodiment, antibodies against mitochondrial antigens (SigmaChemical Co.; Molecular Probes, Inc.; Caltag Antibody Co.) are used tolabel mitochondrial components that are localized in specificmitochondrial domains. Examples of these components are themacromolecules involved in maintaining mitochondrial DNA structure andfunction. DNA, RNA, histones, DNA polymerase, RNA polymerase, andmitochondrial variants of cytoplasmic macromolecules such asmitochondrial tRNA and rRNA are examples mitochondrial antigens. Otherexamples of mitochondrial antigens are the components of the oxidativephosphorylation system found in the mitochondria (e.g., cytochrome c,cytochrome c oxidase, and succinate dehydrogenase).

In a third embodiment, protein chimeras consisting of a mitochondrialprotein genetically fused to an intrinsically luminescent protein suchas the green fluorescent protein, or mutants thereof, are used to labelthe mitochondrial domain. Examples of these components are themacromolecules involved in maintaining mitochondrial DNA structure andfunction. Examples include histones, DNA polymerase, RNA polymerase, andthe components of the oxidative phosphorylation system found in themitochondria (e.g., cytochrome c, cytochrome c oxidase, and succinatedehydrogenase).

Endoplasmic Reticulum Labeling

In one embodiment, membrane permeant endoplasmic reticulum-specificluminescent reagents (Molecular Probes, Inc.) are used to label theendoplasmic reticulum of living and fixed cells. These reagents includeshort chain carbocyanine dyes (e.g., DiOC₆ and DiOC₃), long chaincarbocyanine dyes (e.g. DiIC₁₆ and DiIC₁₈), and luminescently labeledlectins such as concanavalin A.

In a second embodiment, antibodies against endoplasmic reticulumantigens (Sigma Chemical Co.; Molecular Probes, Inc.; Caltag AntibodyCo.) are used to label endoplasmic reticulum components that arelocalized in specific endoplasmic reticulum domains. Examples of thesecomponents are the macromolecules involved in the fatty acid elongationsystems, glucose-6-phosphatase, and HMG CoA-reductase.

In a third embodiment, protein chimeras consisting of a endoplasmicreticulum protein genetically fused to an intrinsically luminescentprotein such as the green fluorescent protein, or mutants thereof, areused to label the endoplasmic reticulum domain. Examples of thesecomponents are the macromolecules involved in the fatty acid elongationsystems, glucose-6-phosphatase, and HMG CoA-reductase.

Golgi Labeling

In one embodiment, membrane permeant Golgi-specific luminescent reagents(Molecular Probes, Inc.) are used to label the Golgi of living and fixedcells. These reagents include luminescently labeled macromolecules suchas wheat germ agglutinin and Brefeldin A as well as luminescentlylabeled ceramide.

In a second embodiment, antibodies against Golgi antigens (SigmaChemical Co.; Molecular Probes, Inc.; Caltag Antibody Co.) are used tolabel Golgi components that are localized in specific Golgi domains.Examples of these components are N-acetylglucosamine phosphotransferase,Golgi-specific phosphodiesterase, and mannose-6-phosphate receptorprotein.

In a third embodiment, protein chimeras consisting of a Golgi proteingenetically fused to an intrinsically luminescent protein such as thegreen fluorescent protein, or mutants thereof, are used to label theGolgi domain. Examples of these components are N-acetylglucosaminephosphotransferase, Golgi-specific phosphodiesterase, andmannose-6-phosphate receptor protein.

While many of the examples presented involve the measurement of singlecellular processes, this is again is intended for purposes ofillustration only. Multiple parameter high-content screens can beproduced by combining several single parameter screens into amultiparameter high-content screen or by adding cellular parameters toany existing high-content screen. Furthermore, while each example isdescribed as being based on either live or fixed cells, eachhigh-content screen can be designed to be used with both live and fixedcells.

Those skilled in the art will recognize a wide variety of distinctscreens that can be developed based on the disclosure provided herein.There is a large and growing list of known biochemical and molecularprocesses in cells that involve translocations or reorganizations ofspecific components within cells. The signaling pathway from the cellsurface to target sites within the cell involves the translocation ofplasma membrane-associated proteins to the cytoplasm. For example, it isknown that one of the src family of protein tyrosine kinases, pp60c-src(Walker et al (1993), J. Biol. Chem. 268:19552-19558) translocates fromthe plasma membrane to the cytoplasm upon stimulation of fibroblastswith platelet-derived growth factor (PDGF). Additionally, the targetsfor screening can themselves be converted into fluorescence-basedreagents that report molecular changes including ligand-binding andpost-translocational modifications.

1. An automated method for analyzing neurite outgrowth comprisingproviding an array of locations comprising cells, wherein the cellspossess at least a first luminescently labeled reporter molecule thatreports on cell location, and at least a second luminescently labeledreporter molecule that reports on neurite outgrowth, and wherein thecells comprise neurons; imaging or scanning multiple cells in each ofthe locations containing multiple cells to obtain luminescent signalsfrom the first and second luminescently-labeled reporter molecule;converting the luminescent signals into digital data; and utilizing thedigital data to automatically make measurements, wherein themeasurements are used to automatically calculate changes in thedistribution, environment or activity of the first and secondluminescently labeled reporter molecules on or within the cells, whereinthe calculated changes provide a measure of neurite outgrowth from theneurons.
 2. The method of claim 1 further comprising contacting theneurons with a test compound, and wherein the calculated changesindicate whether the test compound has modified neurite outgrowth in theneurons.
 3. The method of claim 2, further comprising contacting theneurons with a neurotoxin either before, after, or simultaneously withthe test compound.
 4. The method of claim 1 wherein the firstluminescently labeled reporter molecule comprises a DNA bindingcompound.
 5. The method of claim 1 wherein the second luminescentlylabeled reporter molecule comprises a compound that selectively detectsa cell component selected from the group consisting of cytoplasm,membrane, neuron-specific cell component, and cellular proteins.
 6. Themethod of claim 1, further comprising contacting the cells with acontrol compound known to stimulate neurite outgrowth, and utilizing thecalculated changes to determine whether the test stimulus inhibited thecontrol compound from inducing neurite outgrowth in the neurons.
 7. Themethod of claim 1 wherein the calculated changes are used to identifyconditions that are toxic to neurons and affect neurite morphology. 8.The method of claim 1 wherein the second luminescently labeled reportermolecule is neuron-specific.
 9. The method of claim 1 wherein the arrayof locations containing cells include cells other than neurons, andwherein the neurons possess a neuron-specific luminescent reportermolecule, and wherein the neuron-specific luminescent reporter moleculeis spectrally distinguishable from the first and second luminescentlylabeled reporter molecule.
 10. The method of claim 8 or 9 wherein theneuron-specific luminescent reporter molecule comprises a moleculeselected from the group consisting of neurofilament proteins,βIII-tubulin, ciliary neurotrophic factor, and antibodies specific forneurofilament proteins, βIII-tubulin, ciliary neurotrophic factor. 11.The method of claim 1, wherein the imaging or scanning comprises thesteps of: a. acquiring a nuclear image and a neurite image; b.identifying cell bodies; and c. identifying neurites extending from eachcell body.
 12. The method of claim 11 wherein identifying cell bodiescomprises the steps of: a. generating a kernel image from the nuclearimage; b. performing conditional dilations of the kernel image toidentify the cell body.
 13. The method of claim 12, wherein identifyingneurites extending from cell bodies comprises the steps of: a.generating a reservoir image from the neurite image; and b. identifyingpositive pixels in the reservoir image that are not present in the cellbodies, wherein such positive pixels belong to neurites extending fromcell bodies.
 14. The method of claim 13, further comprising a.performing one conditional dilation of the kernel image to acquire adilation image; b. determining a set of nodes from the dilation image;c. linking together connected nodes; and d. repeating steps (a)-(c)until an entire neurite length has been traced.
 15. The method of any ofclaim 1-9, 11-14, wherein the measurements include one or more of thefollowing: a. Number of cells; b. Number of neurons; c. Total neuritelength from all cells; d. Total number of neurite branches from allcells; e. Number of neurites per cell; f. Number of neurites perpositive neuron g. Neurite length from each cell; h. Neurite length perpositive neuron i. Neurite length per neurite j. Number of cells thatare positive for neurite outgrowth k. Percentage of cells positive forneurite outgrowth; l. cell body area; m. number of branches per neuron;n. number of branches per neurite; or o. Degree of neurite outgrowthfrom a neuron or neuronal cell cluster.
 16. The method of claim 15,wherein the calculated changes include one or more of the following: a.Changes in the number of cells; b. Changes in the number of neurons; c.Changes in the total neurite length from all cells; d. Changes in thetotal number of neurite branches from all cells; e. Changes in thenumber of neurites per cell; f. Changes in the number of neurites perpositive neuron g. Changes in the neurite length from each cell; h.Changes in the neurite length per positive neuron i. Changes in theneurite length per neurite j. Changes in the number of cells that arepositive for neurite outgrowth k. Changes in the percentage of cellspositive for neurite outgrowth; or l. Changes in cell body area; m.Changes in number of branches per neuron; n. Changes in number ofbranches per neurite; or o. Changes in the degree of neurite outgrowthfrom a neuron or neuronal cell cluster.
 17. The method of claim 1,wherein sub-regions of the array of locations containing cells aresampled multiple times at intervals to provide kinetic measurement ofchanges in the distribution, environment or activity of the luminescentreporter molecules on or within the cells
 18. A computer readablestorage medium comprising a program containing a set of instructions forcausing a cell screening system to execute the method of claim 1 whereinthe cell screening system comprises an optical system with a stageadapted for holding a plate containing cells, a means for moving thestage or the optical system, a digital camera, a means for directinglight emitted from the cells to the digital camera, and a computer meansfor receiving and processing the digital data from the digital camera.19. A kit for analyzing neurite outgrowth comprising: (a) at least oneneuron-specific luminescent reporter molecule; (b) a nucleus-specificluminescent reporter molecule; and (c) instructions for using theneuron-specific luminescent reporter molecule and the nucleus-specificluminescent reporter molecule to analyze neurite outgrowth.
 20. The kitof claim 19 wherein the neuron-specific luminescent reporter moleculecomprises a molecule selected from the group consisting of neurofilamentproteins, βIII-tubulin, ciliary neurotrophic factor, and antibodiesspecific for neurofilament proteins, βIII-tubulin, ciliary neurotrophicfactor.